ADA Public Wiki - User contributions [en-gb]

Quick Deposit Guide

2025-07-10T01:12:22Z

RPerry: /* Step 4 - Provide metadata */

= Step 1 - Contact the ADA =
If you want to deposit research data with the ADA, please send an email to '''ada@ada.edu.au''' with the following information:

'''- Study Title:'''
'''- Study Year:'''
'''- Department or Research group: '''
'''- [https://vocabs.ardc.edu.au/viewById/316 Field of Research (FoR) code(s)]: '''
'''- List of Files and File Descriptions:'''

See [[Deposit Appraisal & Collection Policy]] for details on what data the ADA accepts. Licenses and access conditions will be discussed once the deposit is accepted for archiving with the ADA.

= Step 2 - Prepare data files and documentation =
== De-identification of sensitive data ==
Ensure that your data does not contain identifying information about your research participants. This includes, for instance, personal information about the respondents in a survey that could lead to the identification of an individual respondent.

For more information on the topic see:
*[https://docs.ada.edu.au/index.php/Legal_&_Ethical Legal & Ethical]
*[https://docs.ada.edu.au/index.php/De-Identification De-Identification]
*[https://docs.ada.edu.au/index.php/The_Privacy_Act_1988 The Privacy Act 1988]

== Reusability of data ==
Data deposited at the ADA should be understandable and reusable by a secondary user.
''' Please ensure that: '''
'''- Study variable names use a consistent naming convention and can be readily matched to corresponding questions and sections on the study questionnaire (if applicable).'''
'''- All variables have appropriate labels. Labels should enable secondary users to understand the meaning of each variable, and ADA recommends that variable label lengths should be 80 characters or less.'''
'''- All values of categorical variables have clear labels, preferably under 25 characters '''
'''- There are no comma or separators in value labels as this can cause problems in CSV files. Ensure also that any leading or trailing spaces are removed. '''

For more information see:
* [[Qualitative Data Processing]]
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]

== Data formats ==
The ADA prefers SPSS files for tabular survey data because that file format contains a metadata dictionary. Other compatible formats are also generally accepted, provided variable and values labels can be associated with their data. We will export all tabular data to SPSS, STATA and SAS formats, as well as CSV for distribution.

If you are using an unusual format (e.g. a database set up), please let us know in advance and we can discuss options.

For more information see:
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]
* [https://docs.ada.edu.au/index.php/Preservation_plan Preservation plan]

== Documentation files ==
Please provide appropriate documentation for your data. As a minimum, you should supply the study questionnaire (or equivalent research materials that correspond to your data). Other appropriate supporting documentation can include:

* technical report

* instructions to the data collector

Note that related publications with an existing digital identifier (DOI) or webpage (URL) can be referenced in the project metadata on Dataverse.

==Qualitative Data Processing==

Support materials are available for qualitative researchers on this page.
Materials: [https://docs.ada.edu.au/index.php/Qualitative_Data_Processing Qualitative Data Processing]

= Step 3 - Upload files =
An ADA archivist will send you a link to a website where you can securely upload your files. To access this website you will first be directed to create a user account. Please inform the ADA once you have done that step, so we can give you editing rights to your deposit page.

Please upload your data files and supporting documentation files to this site. Alternative file sharing services can be used by prior arrangement with ADA. For security reasons, please do not send data files by email.

= Step 4 - Provide metadata =

Good metadata is essential for findability and reusability of data. Please fill in as many metadata fields as you can in the provided deposit shell (where you uploaded your data). Navigate to the Metadata tab, and click ‘Add + Edit Metadata’ to edit the fields.

See our brief [[Metadata guidelines for ADA Dataverse]]

If you are still unsure about what information to provide in a given field, please refer to the [https://zenodo.org/records/5576412 Dataverse North Metadata Best Practises Guide]

= Step 5 - License and Access conditions =
Before data can be published on the ADA Dataverse, the data rights holder must sign a license agreement with the ADA. This license specifies the conditions under which the ADA can disseminate the data. See the [https://docs.ada.edu.au/index.php/Rights_Management Rights Managment] section on the ADA wiki for more information.

The agreement allows you to specify the terms and conditions of access for data users, the details users must provide, and the process by which data requests will be assessed and approved, see [https://docs.ada.edu.au/index.php/Setting_Access_Conditions Access Conditions] for details. The ADA can advise on what access condition would suit your data.

Quick Deposit Guide

2025-07-10T01:08:43Z

RPerry: /* Step 4 - Provide metadata */

= Step 1 - Contact the ADA =
If you want to deposit research data with the ADA, please send an email to '''ada@ada.edu.au''' with the following information:

'''- Study Title:'''
'''- Study Year:'''
'''- Department or Research group: '''
'''- [https://vocabs.ardc.edu.au/viewById/316 Field of Research (FoR) code(s)]: '''
'''- List of Files and File Descriptions:'''

See [[Deposit Appraisal & Collection Policy]] for details on what data the ADA accepts. Licenses and access conditions will be discussed once the deposit is accepted for archiving with the ADA.

= Step 2 - Prepare data files and documentation =
== De-identification of sensitive data ==
Ensure that your data does not contain identifying information about your research participants. This includes, for instance, personal information about the respondents in a survey that could lead to the identification of an individual respondent.

For more information on the topic see:
*[https://docs.ada.edu.au/index.php/Legal_&_Ethical Legal & Ethical]
*[https://docs.ada.edu.au/index.php/De-Identification De-Identification]
*[https://docs.ada.edu.au/index.php/The_Privacy_Act_1988 The Privacy Act 1988]

== Reusability of data ==
Data deposited at the ADA should be understandable and reusable by a secondary user.
''' Please ensure that: '''
'''- Study variable names use a consistent naming convention and can be readily matched to corresponding questions and sections on the study questionnaire (if applicable).'''
'''- All variables have appropriate labels. Labels should enable secondary users to understand the meaning of each variable, and ADA recommends that variable label lengths should be 80 characters or less.'''
'''- All values of categorical variables have clear labels, preferably under 25 characters '''
'''- There are no comma or separators in value labels as this can cause problems in CSV files. Ensure also that any leading or trailing spaces are removed. '''

For more information see:
* [[Qualitative Data Processing]]
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]

== Data formats ==
The ADA prefers SPSS files for tabular survey data because that file format contains a metadata dictionary. Other compatible formats are also generally accepted, provided variable and values labels can be associated with their data. We will export all tabular data to SPSS, STATA and SAS formats, as well as CSV for distribution.

If you are using an unusual format (e.g. a database set up), please let us know in advance and we can discuss options.

For more information see:
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]
* [https://docs.ada.edu.au/index.php/Preservation_plan Preservation plan]

== Documentation files ==
Please provide appropriate documentation for your data. As a minimum, you should supply the study questionnaire (or equivalent research materials that correspond to your data). Other appropriate supporting documentation can include:

* technical report

* instructions to the data collector

Note that related publications with an existing digital identifier (DOI) or webpage (URL) can be referenced in the project metadata on Dataverse.

==Qualitative Data Processing==

Support materials are available for qualitative researchers on this page.
Materials: [https://docs.ada.edu.au/index.php/Qualitative_Data_Processing Qualitative Data Processing]

= Step 3 - Upload files =
An ADA archivist will send you a link to a website where you can securely upload your files. To access this website you will first be directed to create a user account. Please inform the ADA once you have done that step, so we can give you editing rights to your deposit page.

Please upload your data files and supporting documentation files to this site. Alternative file sharing services can be used by prior arrangement with ADA. For security reasons, please do not send data files by email.

= Step 4 - Provide metadata =

Good metadata is essential for findability and reusability of data. Please fill in as many metadata fields as you can in the provided deposit shell (where you uploaded your data). Navigate to the Metadata tab, and click ‘Add + Edit Metadata’ to edit the fields.

See [[Metadata guidelines for ADA Dataverse]]

If you are unsure about what information to provide in a given field, please see this detailed guide: https://zenodo.org/records/5576412

= Step 5 - License and Access conditions =
Before data can be published on the ADA Dataverse, the data rights holder must sign a license agreement with the ADA. This license specifies the conditions under which the ADA can disseminate the data. See the [https://docs.ada.edu.au/index.php/Rights_Management Rights Managment] section on the ADA wiki for more information.

The agreement allows you to specify the terms and conditions of access for data users, the details users must provide, and the process by which data requests will be assessed and approved, see [https://docs.ada.edu.au/index.php/Setting_Access_Conditions Access Conditions] for details. The ADA can advise on what access condition would suit your data.

Metadata guidelines for ADA Dataverse

2025-07-09T03:22:43Z

RPerry:

← [[https://docs.ada.edu.au/index.php/Quick_Deposit_Guide#Step_4| Back to Quick Deposit Guide]]

Good metadata makes your dataset findable, citable, and reusable. It tells future users—including you—what the data are, who created them, and how they may be used. Complete the fields below as accurately as you can; richer descriptions mean greater impact.

= Steps for Depositors =

== Accessing the metadata fields ==
The metadata fields can be accessed by:
[[File:Accessing the Dataset Metadata fields.JPG|500px|right]]

1. Navigate to the metadata section on your deposit page, by selecting the "Metadata" Tab, followed by the "Add + Edit Metadata" button.

This will open up the dataset metadata fields ready for review and population.

== Populating the Metadata fields ==

2. Review and populate the Metadata fields.

;SECTION A. Citation metadata (always complete)
* '''Project title''' – ''Required''. Clear, descriptive title. *Example:* Australian Election Study 2025
* '''Author''' – ''Required''. Lead researcher(s) in “Family, Given” order; add ORCID if known.
* '''Contact''' – ''Required''. Person or group who can answer questions (email only is fine).
* '''Description''' – ''Required''. 2–4 sentences on what the dataset contains, why it was collected, and key methods.
* '''Subject''' – ''Required''. Choose the closest category from the drop-down list.
* '''Keyword''' – ''Recommended''. Add 3–5 terms from a controlled vocabulary (e.g. ANZSRC, ELSST).
* '''Topic classification (ANZSRC FoR code)''' – ''Recommended''. 4- or 6-digit code plus description (e.g. 160601 – Australian Government and Politics).
* '''Related publication''' – ''Optional''. Full citation and DOI if a paper already uses the data.
* '''Notes''' – ''Optional''. Short, important notices only (e.g. ethics approval number, copyright statement).
* '''Language''' – ''Recommended''. Primary language of the data (usually English).
* '''Time period covered''' – ''Recommended''. Start and end dates the data refer to.
* '''Date of collection''' – ''Optional''. When the data were gathered.
* '''Kind of data''' – ''Optional''. Brief type description (e.g. Survey data, Administrative records).

[[File:MetadataSection1.jpg|400px|right]]
;SECTION B. Geospatial metadata (fill in if your data have a location element)
* '''Geographic coverage''' – ''Recommended''. Country, region, or coordinates covered.
* '''Geographic unit''' – ''Optional''. Finer units such as postcode or mesh block.
* '''Bounding box''' – ''Optional''. Use the map tool if exact bounds are important.

;SECTION C. Social science & humanities metadata (only if relevant)
* '''Series''' – ''Optional''. Name the study series if this dataset is part of one (e.g. HILDA Wave 20).
* '''Grant information''' – ''Optional''. Funder name and grant number.
* '''Software''' – ''Optional''. Software and version needed to read the files (e.g. SPSS v29).
* '''Related material / datasets''' – ''Optional''. Links or citations to questionnaires, codebooks, or previous waves.

== Completion ==

3. Save changes and notify ADA
[[File: Savechanges.jpg|300px|right]]
# Click <code>Save changes</code>.
# Submit your files as instructed.
# Notify ADA once these steps are completed and we will review your submission.

== Quick-reference table ==

{| class="wikitable"
! Field !! Status
|-
| Project title || Required
|-
| Author || Required
|-
| Contact || Required
|-
| Description || Required
|-
| Subject || Required
|-
| Keyword || Recommended
|-
| Topic classification (ANZSRC FoR) || Recommended
|-
| Language || Recommended
|-
| Time period covered || Recommended
|-
| Related publication || Optional
|-
| Notes || Optional
|-
| Date of collection || Optional
|-
| Kind of data || Optional
|-
| Geographic coverage || Recommended†
|-
| Geographic unit || Optional†
|-
| Bounding box || Optional†
|-
| Series || Optional‡
|-
| Grant information || Optional‡
|-
| Software || Optional‡
|-
| Related material / datasets || Optional‡
|}

''† Only for datasets with spatial content • ‡ Social-science block (visible when “Add + Edit Metadata” ▶ Social Science & Humanities)''

== Need help? ==
Email us at [mailto:support@ada.edu.au support@ada.edu.au] and an archivist will get back to you.

Metadata guidelines for ADA Dataverse

2025-07-09T03:20:22Z

RPerry:

= Dataverse metadata quick guide =

← [[https://docs.ada.edu.au/index.php/Quick_Deposit_Guide#Step_4| Back to Quick Deposit Guide]]

Good metadata makes your dataset findable, citable, and reusable. It tells future users—including you—what the data are, who created them, and how they may be used. Complete the fields below as accurately as you can; richer descriptions mean greater impact.

= Steps for Depositors =

== Accessing the metadata fields ==
The metadata fields can be accessed by:
[[File:Accessing the Dataset Metadata fields.JPG|500px|right]]

1. Navigate to the metadata section on your deposit page, by selecting the "Metadata" Tab, followed by the "Add + Edit Metadata" button.

This will open up the dataset metadata fields ready for review and population.

== Populating the Metadata fields ==

2. Review and populate the Metadata fields.

;SECTION A. Citation metadata (always complete)
* '''Project title''' – ''Required''. Clear, descriptive title. *Example:* Australian Election Study 2025
* '''Author''' – ''Required''. Lead researcher(s) in “Family, Given” order; add ORCID if known.
* '''Contact''' – ''Required''. Person or group who can answer questions (email only is fine).
* '''Description''' – ''Required''. 2–4 sentences on what the dataset contains, why it was collected, and key methods.
* '''Subject''' – ''Required''. Choose the closest category from the drop-down list.
* '''Keyword''' – ''Recommended''. Add 3–5 terms from a controlled vocabulary (e.g. ANZSRC, ELSST).
* '''Topic classification (ANZSRC FoR code)''' – ''Recommended''. 4- or 6-digit code plus description (e.g. 160601 – Australian Government and Politics).
* '''Related publication''' – ''Optional''. Full citation and DOI if a paper already uses the data.
* '''Notes''' – ''Optional''. Short, important notices only (e.g. ethics approval number, copyright statement).
* '''Language''' – ''Recommended''. Primary language of the data (usually English).
* '''Time period covered''' – ''Recommended''. Start and end dates the data refer to.
* '''Date of collection''' – ''Optional''. When the data were gathered.
* '''Kind of data''' – ''Optional''. Brief type description (e.g. Survey data, Administrative records).

[[File:MetadataSection1.jpg|400px|right]]
;SECTION B. Geospatial metadata (fill in if your data have a location element)
* '''Geographic coverage''' – ''Recommended''. Country, region, or coordinates covered.
* '''Geographic unit''' – ''Optional''. Finer units such as postcode or mesh block.
* '''Bounding box''' – ''Optional''. Use the map tool if exact bounds are important.

;SECTION C. Social science & humanities metadata (only if relevant)
* '''Series''' – ''Optional''. Name the study series if this dataset is part of one (e.g. HILDA Wave 20).
* '''Grant information''' – ''Optional''. Funder name and grant number.
* '''Software''' – ''Optional''. Software and version needed to read the files (e.g. SPSS v29).
* '''Related material / datasets''' – ''Optional''. Links or citations to questionnaires, codebooks, or previous waves.

== Completion ==

3. Save changes and notify ADA
[[File: Savechanges.jpg|300px|right]]
# Click <code>Save changes</code>.
# Submit your files as instructed.
# Notify ADA once these steps are completed and we will review your submission.

== Quick-reference table ==

{| class="wikitable"
! Field !! Status
|-
| Project title || Required
|-
| Author || Required
|-
| Contact || Required
|-
| Description || Required
|-
| Subject || Required
|-
| Keyword || Recommended
|-
| Topic classification (ANZSRC FoR) || Recommended
|-
| Language || Recommended
|-
| Time period covered || Recommended
|-
| Related publication || Optional
|-
| Notes || Optional
|-
| Date of collection || Optional
|-
| Kind of data || Optional
|-
| Geographic coverage || Recommended†
|-
| Geographic unit || Optional†
|-
| Bounding box || Optional†
|-
| Series || Optional‡
|-
| Grant information || Optional‡
|-
| Software || Optional‡
|-
| Related material / datasets || Optional‡
|}

''† Only for datasets with spatial content • ‡ Social-science block (visible when “Add + Edit Metadata” ▶ Social Science & Humanities)''

== Need help? ==
Email us at [mailto:support@ada.edu.au support@ada.edu.au] and an archivist will get back to you.

Metadata guidelines for ADA Dataverse

2025-07-09T03:11:55Z

RPerry: Created page with "= Dataverse metadata quick guide = ← Back to Quick Deposit Guide Good metadata makes your dataset findable, citable, and reusable. It tells future users—including you—what the data are, who created them, and how they may be used. Complete the fields below as accurately as you can; richer descriptions mean greater impact. = Steps for Depositors = == Accessing the metadata fields == The metad..."

= Dataverse metadata quick guide =

← [[https://docs.ada.edu.au/index.php/Quick_Deposit_Guide#Step_4| Back to Quick Deposit Guide]]

Good metadata makes your dataset findable, citable, and reusable. It tells future users—including you—what the data are, who created them, and how they may be used. Complete the fields below as accurately as you can; richer descriptions mean greater impact.

= Steps for Depositors =

== Accessing the metadata fields ==
The metadata fields can be accessed by:
[[File:Accessing the Dataset Metadata fields.JPG|500px|right]]

1. Navigate to the metadata section on your deposit page, by selecting the "Metadata" Tab, followed by the "Add + Edit Metadata" button.

This will open up the dataset metadata fields ready for review and population.

== Populating the Metadata fields ==

2. Review and populate the Metadata fields.

;SECTION A. Citation metadata (always complete)
* '''Project title''' – ''Required''. Clear, descriptive title. *Example:* Australian Election Study 2025
* '''Author''' – ''Required''. Lead researcher(s) in “Family, Given” order; add ORCID if known.
* '''Contact''' – ''Required''. Person or group who can answer questions (email only is fine).
* '''Description''' – ''Required''. 2–4 sentences on what the dataset contains, why it was collected, and key methods.
* '''Subject''' – ''Required''. Choose the closest category from the drop-down list.
* '''Keyword''' – ''Recommended''. Add 3–5 terms from a controlled vocabulary (e.g. ANZSRC, ELSST).
* '''Topic classification (ANZSRC FoR code)''' – ''Recommended''. 4- or 6-digit code plus description (e.g. 160601 – Australian Government and Politics).
* '''Related publication''' – ''Optional''. Full citation and DOI if a paper already uses the data.
* '''Notes''' – ''Optional''. Short, important notices only (e.g. ethics approval number, copyright statement).
* '''Language''' – ''Recommended''. Primary language of the data (usually English).
* '''Time period covered''' – ''Recommended''. Start and end dates the data refer to.
* '''Date of collection''' – ''Optional''. When the data were gathered.
* '''Kind of data''' – ''Optional''. Brief type description (e.g. Survey data, Administrative records).

[[File:MetadataSection1.jpg|400px|right]]
;SECTION B. Geospatial metadata (fill in if your data have a location element)
* '''Geographic coverage''' – ''Recommended''. Country, region, or coordinates covered.
* '''Geographic unit''' – ''Optional''. Finer units such as postcode or mesh block.
* '''Bounding box''' – ''Optional''. Use the map tool if exact bounds are important.

;SECTION C. Social science & humanities metadata (only if relevant)
* '''Series''' – ''Optional''. Name the study series if this dataset is part of one (e.g. HILDA Wave 20).
* '''Grant information''' – ''Optional''. Funder name and grant number.
* '''Software''' – ''Optional''. Software and version needed to read the files (e.g. SPSS v29).
* '''Related material / datasets''' – ''Optional''. Links or citations to questionnaires, codebooks, or previous waves.

== Completion ==

3. Save changes and notify ADA
[[File: Savechanges.jpg|300px|right]]
# Click <code>Save changes</code>.
# Submit your files as instructed.
# You will receive a DOI once ADA archivists have completed their review.

== Quick-reference table ==

{| class="wikitable"
! Field !! Status
|-
| Project title || Required
|-
| Author || Required
|-
| Contact || Required
|-
| Description || Required
|-
| Subject || Required
|-
| Keyword || Recommended
|-
| Topic classification (ANZSRC FoR) || Recommended
|-
| Language || Recommended
|-
| Time period covered || Recommended
|-
| Related publication || Optional
|-
| Notes || Optional
|-
| Date of collection || Optional
|-
| Kind of data || Optional
|-
| Geographic coverage || Recommended†
|-
| Geographic unit || Optional†
|-
| Bounding box || Optional†
|-
| Series || Optional‡
|-
| Grant information || Optional‡
|-
| Software || Optional‡
|-
| Related material / datasets || Optional‡
|}

''† Only for datasets with spatial content • ‡ Social-science block (visible when “Add + Edit Metadata” ▶ Social Science & Humanities)''

== Need help? ==
Email us at [mailto:support@ada.edu.au support@ada.edu.au] and an archivist will get back to you.

File:Savechanges.jpg

2025-07-09T03:05:09Z

RPerry: RPerry uploaded a new version of File:Savechanges.jpg

File:Savechanges.jpg

2025-07-09T03:01:20Z

RPerry:

File:MetadataSection1.jpg

2025-07-09T02:55:56Z

RPerry:

Quick Deposit Guide

2025-07-09T02:34:57Z

RPerry:

= Step 1 - Contact the ADA =
If you want to deposit research data with the ADA, please send an email to '''ada@ada.edu.au''' with the following information:

'''- Study Title:'''
'''- Study Year:'''
'''- Department or Research group: '''
'''- [https://vocabs.ardc.edu.au/viewById/316 Field of Research (FoR) code(s)]: '''
'''- List of Files and File Descriptions:'''

See [[Deposit Appraisal & Collection Policy]] for details on what data the ADA accepts. Licenses and access conditions will be discussed once the deposit is accepted for archiving with the ADA.

= Step 2 - Prepare data files and documentation =
== De-identification of sensitive data ==
Ensure that your data does not contain identifying information about your research participants. This includes, for instance, personal information about the respondents in a survey that could lead to the identification of an individual respondent.

For more information on the topic see:
*[https://docs.ada.edu.au/index.php/Legal_&_Ethical Legal & Ethical]
*[https://docs.ada.edu.au/index.php/De-Identification De-Identification]
*[https://docs.ada.edu.au/index.php/The_Privacy_Act_1988 The Privacy Act 1988]

== Reusability of data ==
Data deposited at the ADA should be understandable and reusable by a secondary user.
''' Please ensure that: '''
'''- Study variable names use a consistent naming convention and can be readily matched to corresponding questions and sections on the study questionnaire (if applicable).'''
'''- All variables have appropriate labels. Labels should enable secondary users to understand the meaning of each variable, and ADA recommends that variable label lengths should be 80 characters or less.'''
'''- All values of categorical variables have clear labels, preferably under 25 characters '''
'''- There are no comma or separators in value labels as this can cause problems in CSV files. Ensure also that any leading or trailing spaces are removed. '''

For more information see:
* [[Qualitative Data Processing]]
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]

== Data formats ==
The ADA prefers SPSS files for tabular survey data because that file format contains a metadata dictionary. Other compatible formats are also generally accepted, provided variable and values labels can be associated with their data. We will export all tabular data to SPSS, STATA and SAS formats, as well as CSV for distribution.

If you are using an unusual format (e.g. a database set up), please let us know in advance and we can discuss options.

For more information see:
* [https://docs.ada.edu.au/index.php/Quality_Assurance Quality Assurance]
* [https://docs.ada.edu.au/index.php/Workflows Workflows]
* [https://docs.ada.edu.au/index.php/Preservation_plan Preservation plan]

== Documentation files ==
Please provide appropriate documentation for your data. As a minimum, you should supply the study questionnaire (or equivalent research materials that correspond to your data). Other appropriate supporting documentation can include:

* technical report

* instructions to the data collector

Note that related publications with an existing digital identifier (DOI) or webpage (URL) can be referenced in the project metadata on Dataverse.

==Qualitative Data Processing==

Support materials are available for qualitative researchers on this page.
Materials: [https://docs.ada.edu.au/index.php/Qualitative_Data_Processing Qualitative Data Processing]

= Step 3 - Upload files =
An ADA archivist will send you a link to a website where you can securely upload your files. To access this website you will first be directed to create a user account. Please inform the ADA once you have done that step, so we can give you editing rights to your deposit page.

Please upload your data files and supporting documentation files to this site. Alternative file sharing services can be used by prior arrangement with ADA. For security reasons, please do not send data files by email.

= Step 4 - Provide metadata =

Good metadata is essential for findability and reusability of data. Please fill in as many metadata fields as you can in the provided deposit shell (where you uploaded your data). Navigate to the Metadata tab, and click ‘Add + Edit Metadata’ to edit the fields.

See [[Metadata guidelines for ADA Dataverse]]

If you are unsure about what information to provide in a given field, please contact the ADA for guidance.

= Step 5 - License and Access conditions =
Before data can be published on the ADA Dataverse, the data rights holder must sign a license agreement with the ADA. This license specifies the conditions under which the ADA can disseminate the data. See the [https://docs.ada.edu.au/index.php/Rights_Management Rights Managment] section on the ADA wiki for more information.

The agreement allows you to specify the terms and conditions of access for data users, the details users must provide, and the process by which data requests will be assessed and approved, see [https://docs.ada.edu.au/index.php/Setting_Access_Conditions Access Conditions] for details. The ADA can advise on what access condition would suit your data.

Security

2024-09-14T02:51:37Z

RPerry: /* References */

== Security Levels ==
The four primary ADA Dataverse installations are deployed on NCI VMware servers and are secured and monitored by NCI [7], and ANU ITS and CIO services [52]. Access to the VMs is controlled by NCI – the ADA Technical Manager requests when specific users should be given SSH access, with what privileges, and when they should be removed.

Access to ADA’s NCI-hosted remote desktop service (RDS) is through an NCI-managed GlobalProtect VPN ADA-specific group. The ADA Technical Manager communicates with NCI to request ADA employees be added to and removed from that group as needed when onboarding and offboarding employees.

The Dataverse backend PostgreSQL database ports are locked down to restrict access. NCI and the ADA DevOps manage access to these ports.

The ADA Dataverse installations are protected as much as possible by a conservative f5 WAF [55] that is tuned as needed. Suspicious activity that the WAF catches is blocked, monitored and reported to the ADA technical team. NCI implements an automated weekly scan of ADA services including Dataverse installations and sends a report to the ADA team highlighting potential and real security issues. The ADA DevOps is responsible for addressing those security issues and reporting any that remain unresolved.

The four primary Dataverse installations are protected as much as possible by a conservative f5 WAF [55] that is tuned as needed. Suspicious activity that the WAF can catch is blocked, monitored and reported to the ADA technical team. NCI implements an automated weekly scan of ADA’s services including Dataverse installations and sends a report to the ADA team, plus others, highlighting potential, and real, security issues. The ADA DevOps is responsible for addressing those that are possible to address and reporting back on those that are not. The SIP/AIP/DIP files reside on NCI storage (server). This is protected by NCI standard protocols.

== Security Measures ==
* IT security is implemented by NCI and ANU Information Technology Services (ITS) [52].
* Risk analysis lies with NCI and ITS.
* Risk analysis relative to level of data sensitivity is undertaken by the ADA Archivist team.

According to the Australian Government Security Classification System, data archived at ADA is deemed as UNCLASSIFIED - DLM (dissemination limiting marker). The DLM would be 'Sensitive' or Sensitive-Personal'. - Protective Security Policy Framework [56]. Any data that is deemed too high risk to be made available for download through Dataverse is requested through Dataverse, but the data transfer is completed through an external service AARNET File Sender [57].

== Security for the Facility & Digital Objects Premises ==
IT security and risk analysis is implemented by NCI and ANU Information Technology Services (ITS) [52].

Risk analysis relative to level of data sensitivity is undertaken by the ADA Archivist team. Any data that is deemed too high risk to be made available for download through Dataverse is requested through Dataverse, but the data transfer is completed through an external service – AARNET File Sender [57].

The ADA office is secured and accessible by ANU-issues staff card access for ADA staff only. The access card is an ANU centrally controlled photo identity security system. All secure physical data objects are stored in a locked safe in a locked storeroom, or locked cupboard in a second locked office within ADA. Computer screens are locked while staff are absent from their desks.

NCI servers are protected according to NCI standards. NCI is based in a secure building on ANU campus accessible to authorised NCI staff only. Approved visitors must be signed in, wear visitor identification, and be accompanied by NCI staff.

The ADA complies with ANU policy for Information technology security [58] and Code of Conduct [59].

== Authentication & Authorisation==
Dataverse maintains CoreTrustSeal appropriate application-level security and user authentication [60].

Access to ANU infrastructure is restricted to students or staff members of the ANU. Roles and corresponding system privileges are managed by the ANU ITS team [58].

Access to the NCI infrastructure requires a NCI user account. Users who wish access to NCI infrastructure must apply for an NCI Project to be created. That request is approved or rejected by NCI administrators. The Project owner/manager must grant access to specific NCI user accounts to allow those user accounts access. NCI user accounts are forced to be reasserted and a new password created every 6 months.

Access to data for the ADA archiving team is through the secure NCI RDS set up specifically for ADA. The ADA RDS is behind the NCI f5 firewall where it has direct access to the ADA data storage also managed by NCI. The ADA RDS requires GlobalProtect [61] VPN to login, and to be a member of a specific GlobalProtect group. The ADA Technical Manager requests a new ADA archivist to be added to the group when they begin employment and requests removal when an employee leaves.

== References ==
[39] Security - (https://docs.ada.edu.au/index.php/Security)

[58] ANU Policy: Information technology security – (https://policies.anu.edu.au/ppl/document/ANUP_000421)

[59] ANU Policy: Code of Conduct – (https://policies.anu.edu.au/ppl/document/ANUP_000388)

[60] Dataverse Security – (https://dataverse.org/book/security)

[61] Global Protect – (https://www.paloaltonetworks.com.au/sase/globalprotect)[7] National Computational Infrastructure – (https://nci.org.au/)

[52] ANU ITS – (https://services.anu.edu.au/business-units/information-technology-services)

[55] F5 – (https://www.f5.com/)

Technical Infrastructure

2024-09-14T02:44:34Z

RPerry: /* References */

== Repository Software ==
The ADA implements the OAIS Reference Model [42] with deployed Dataverse [49] installations for the SIP (deposit.ada.edu.au), AIP (dataverse-test.ada.edu.au) and DIP (dataverse.ada.edu.eu). The Dataverse Project [49] is open source and community-supported code. The Dataverse team has described how the Dataverse software meets CoreTrustSeal Technical Infrastructure requirements [50].

ADA also implements web-based tools, developed and maintained in-house, to support its archiving process:
* Curation and Risk Assessment Tool (CARAT) [73]
* ADA Deposit and Preservation Tool (ADAPT) [6]
* Ingest Reporting Tool (upload of SPSS, generates data dictionary, quality check, confidentiality check) [74]

Access management for data access requests from both dataverse.ada.edu.au and anu-dataverse.ada.edu.au production DIP instances is managed through Osticket [51] ticketing opensource software, with access being Granted or Rejected in Dataverse itself by adding file permissions for approved users. Osticket as a service is required to be available to the same extent as Dataverse to be able to manage access requests.

==Version Control ==
The Harvard Dataverse Project team uses GitHub [54] for its version control system. Any tools or software that ADA produces internally are managed through GitHub.

==IT Service Management ==
Due to its simplicity when compared to the ITIL Service Management framework, the YASM Service Management framework has been initiated by the ADA Technical Manager. As part of this YASM framework, a Service Portfolio has been created, to record and track ADA’s various internal and external services.

At the end of every calendar month, the ADA DevOps role performs updates and maintenance tasks on all of ADA’s services, to keep code and applications up to date. A simple Change Management approach is taken to inform the internal ADA team and external Dataverse users of changes that will be implemented with upcoming Dataverse upgrades. ADA maintains Dataverse installations whose sole purpose is to test changes in new Dataverse releases before pushing the update to ADA’s three primary publicly consumed installations. ADA plans the release schedule of new Dataverse versions in step with the Dataverse Project’s releases. Not all available functionality is desired for ADA so any new functionality is tested and evaluated to determine when to enable it.

NCI performs an automated weekly set of security tests on ADA’s NCI-hosted services. A report with any identified issues is emailed to the ADA technical team and to the ADA Director. The ADA technical team carries out maintenance to address the report-identified issues. ADA services are also monitored by the ANU Chief Information Office (CIO) [52], and ADA receives emails that alert the ADA team to any discovered problems, with a request to address them.

==Infrastructure Standards ==
ANU and NCI [7] have security standards in place to prevent ANU and NCI technical infrastructure from being adversely affected. NCI monitors the primary Dataverse installations with its f5 WAF [55] service.

== Availability, Bandwidth & Connectivity ==
The ADA Dataverse installations are available 24/7. Requests are prioritised and managed within the time capabilities of the ADA Access Management team. Messaging is posted to the ADA’s website and production Dataverse instances to alert users to future ADA shutdowns, to allow users to submit data access requests in a timely manner.

NCI manages network availability and bandwidth for ADA’s NCI-hosted services. NCI also manages its f5 WAF that provides a level of protection for the Dataverse installations.

ANU’s central ITS services [52] manage the domains for each Dataverse installation as well as DNS updates for any services not behind the f5 WAF. ITS is responsible for monitoring the domain registrations, to ensure they are renewed before services become unavailable when a domain registration expires.

NCI manages SSL certificates for ADA’s web-based services and inform the ADA technical team when SSL certificates are about to expire, reissuing them for installing on ADA’s virtual machines (VM).

The ADA technical team has implemented monitors that detect when ADA’s VMs go offline, sending an email to the ADA Director, Technical Manager and DevOps roles. The ADA Devops and Technical Manager work to get the systems back online, consulting with NCI if necessary.

ADA is alerted to planned NCI infrastructure outages. The ADA team posts messaging on the Dataverse installations, and the ADA website, that the systems will be offline on the specified date(s) and time(s).

==Disaster recovery==
Hourly snapshots of ADA’s NCI storage are taken, as well as snapshots/backups of ADA’s Dataverse installations including the Dataverses’ local file storage. Backups of the Dataverse databases are created on their specific VM and stored for 3 months. NCI can restore the ADA project storage from regular backups. If any Dataverse installation has to be re-deployed from a snapshot, the ADA Devops role works in conjunction with NCI to get them back up and running with the most recent snapshot.

NCI is consulted on any issues with SSL certificates and may inform the ADA team to consult ANU ITS. ANU ITS is also consulted on issues relating to the domain.

== Technical Change ==
The Dataverse GitHub repo is monitored for new releases. The ADA staff are also members of the Dataverse User Community [19] and are made aware of new releases via that group as well. Any Dataverse bugs or new features needed by ADA are documented by the ADA Technical Manager on the Dataverse GitHub repo.

Any technical changes relating to Preservation and/or Reuse identified by the Archivist Team are brought up with the ADA Technical Team on an as-needed case-by-case basis. The technical change is discussed and evaluated as to whether it is required and possible to implement. If the ADA technical team can implement the needed change, the team manages it in consultation with the Archivist team. The ADA technical team consults with identified external sources to implement changes where required.

Any Dataverse feature requests for functionality deemed missing according to ADA requirements are created as an issue in the Dataverse GitHub [53] for consideration.

==References==
[38] Technical Infrastructure - (https://docs.ada.edu.au/index.php/Technical_Infrastructure)

[50] Dataverse support for CTS – (https://dataverse.org/book/technical-infrastructure)

[51] osTicket – (https://github.com/osTicket/osTicket)

[52] ANU ITS – (https://services.anu.edu.au/business-units/information-technology-services)

[53] Dataverse GitHub – (https://github.com/IQSS/dataverse/issues)

[54] GitHub – (https://github.com)[55] F5 – (https://www.f5.com/)

[42] Open Archival Information System (OAIS) Reference Model – (https://public.ccsds.org/pubs/650x0m2.pdf)

[49] The Dataverse Project – (https://dataverse.org)

[6] ADAPT – (https://docs.ada.edu.au/index.php/ADAPT)

[73] ADA CARAT tool – (https://github.com/ADA-ANU/ADA_Research_Data_Tools/tree/main/ADA_DRAT_v2)

[74] ADA Ingest Reporting Tool – (https://github.com/ADA-ANU/ADA_Research_Data_Tools/tree/main/ADA_reports)

[7] National Computational Infrastructure – (https://nci.org.au/)

[19] Dataverse User Community – (https://groups.google.com/g/dataverse-community?pli=1)

Quality Assurance

2024-09-14T02:26:51Z

RPerry: /* References */

= Data and Metadata Assessment =
TThe ADA expects a data deposit to meet quality requirements specified in the ADA deposit guidelines [5]. All deposits are assessed for quality assurance by an ADA archivist. This assessment includes both content and form. On the content side, the archivist will examine the data for presence of direct and indirect identifiers. On the form side, the archivist will confirm unambiguous, clear labels for all variables and run spell checks and basic metadata consistency and completeness checks. The archivist will then propose any corresponding changes to the depositor in a formal report. If the depositor does not agree to changes the ADA archivist deems necessary, a deposit may be rejected (see R08 Deposit & Appraisal). If approved by the depositor, the archivist will implement the agreed changes and generate publication-ready versions of the data. All deposits are subject to data-level curation (see R00 Background, part 5).

Accompanying documentation should be submitted to ensure comprehension of the study and the data. The archivist will liaise with the depositor to ensure all necessary value labels and codes are defined, that DDI-Codebook metadata fields are completed on Dataverse, and that the data is maximally findable and reusable. It is not a requirement that a depositor completes all DDI fields, but it is imperative to meet a minimum requirement for reuse as determined by the ADA. The ADA also encourages depositors to include references for related publications and other digital resources in their project metadata on Dataverse.

= Vocabulary & Classification =
The ADA uses [http://vocabularyserver.com/apais/ APAIS] vocabulary for keywords in the Dataverse catalogue, as well as [http://purl.org/au-research/vocabulary/anzsrc-for/2008/16 ANZSRC FoR] codes for topic classification.

= References =
[5] Deposit guidelines – (https://docs.ada.edu.au/index.php/Quick_Deposit_Guide)

[33] Quality Assurance – (https://docs.ada.edu.au/index.php/Quality_Assurance)

Deposit Appraisal & Collection Policy

2024-09-14T02:23:07Z

RPerry: /* Submission appraisal criteria */

==Submission appraisal criteria==
The ADA accepts data that fits broadly into the remit of the archive and can be described with the social science DDI metadata. Submissions must be of current value or of potential historical interest to the ADA. The subject matter being in either the Social, Political or Economic areas, and their many affiliated research fields. The ADA encourages submission of full project data and not just the data associated with a publication release, which is often only a small subset of the actual data available. Submissions must have the potential for secondary analysis using the digital data files and their supporting material. At least a portion of the submissions needs to be made publicly accessible. However, tightly controlled access conditions may apply even to that portion.

==Out of scope materials==
The ADA will only accept digital material. There are no other firm rules regarding the material that won’t be accepted by the ADA for preservation and dissemination, however submissions that contain explicit or offensive material and those that offer limited potential for secondary analysis will not be considered favorably. In addition, submissions that pose significant risk of re-identification may also be rejected where the depositor (and/or the data rights-holder) is unwilling to apply appropriate data or other protections as recommended by ADA staff. Materials submitted may also not be accepted if the metadata provided is insufficient for long-term preservation. This includes the social science DDI metadata on ADA Dataverse, as well as variable-level metadata for all files submitted and all data variables. The ADA will work with depositors to ensure metadata is complete at all levels. Finally, in the event that the ADA determines that the material is not suitable for archiving, it will endeavour to provide the depositor with suggestions of other suitable repositories. The final decision about acceptance of a submission lies with the ADA Director.

==Preferred data formats==
The ADA accepts most formats. However, for tabular data files, the ADA prefers submission in SPSS format (.sav files). This format captures variable level metadata (variable and value labels, data formats etc.) and SPSS Statistics is adept at exporting multiple alternative file formats. The ADA also accepts Stata (.dta) SAS (.sas; .sas7bdat), and R (.rdata), as well as text formats (.csv; .tab) provided data including both value labels and codes can be provided. Other data formats will be considered on a case-by-case basis. For qualitative data, data formats vary significantly and submitted formats will also be considered on a case-by-case basis.

==References ==
[22] Deposit Appraisal & Collection Policy – (https://docs.ada.edu.au/index.php/Deposit_Appraisal_%26_Collection_Policy)

Deposit Appraisal & Collection Policy

2024-09-14T02:22:56Z

RPerry:

==Submission appraisal criteria==
The ADA accepts data that fits broadly into the remit of the archive and can be described with the social science DDI metadata. Submissions must be of current value or of potential historical interest to the ADA. The subject matter being in either the Social, Political or Economic areas, and their many affiliated research fields. The ADA encourages submission of full project data and not just the data associated with a publication release, which is often only a small subset of the actual data available. Submissions must have the potential for secondary analysis using the digital data files and their supporting material. At least a portion of the submissions needs to be made publicly accessible. However, tightly controlled access conditions may apply even to that portion.

==Out of scope materials
The ADA will only accept digital material. There are no other firm rules regarding the material that won’t be accepted by the ADA for preservation and dissemination, however submissions that contain explicit or offensive material and those that offer limited potential for secondary analysis will not be considered favorably. In addition, submissions that pose significant risk of re-identification may also be rejected where the depositor (and/or the data rights-holder) is unwilling to apply appropriate data or other protections as recommended by ADA staff. Materials submitted may also not be accepted if the metadata provided is insufficient for long-term preservation. This includes the social science DDI metadata on ADA Dataverse, as well as variable-level metadata for all files submitted and all data variables. The ADA will work with depositors to ensure metadata is complete at all levels. Finally, in the event that the ADA determines that the material is not suitable for archiving, it will endeavour to provide the depositor with suggestions of other suitable repositories. The final decision about acceptance of a submission lies with the ADA Director.

==Preferred data formats==
The ADA accepts most formats. However, for tabular data files, the ADA prefers submission in SPSS format (.sav files). This format captures variable level metadata (variable and value labels, data formats etc.) and SPSS Statistics is adept at exporting multiple alternative file formats. The ADA also accepts Stata (.dta) SAS (.sas; .sas7bdat), and R (.rdata), as well as text formats (.csv; .tab) provided data including both value labels and codes can be provided. Other data formats will be considered on a case-by-case basis. For qualitative data, data formats vary significantly and submitted formats will also be considered on a case-by-case basis.

==References ==
[22] Deposit Appraisal & Collection Policy – (https://docs.ada.edu.au/index.php/Deposit_Appraisal_%26_Collection_Policy)

Provenance and authenticity

2024-09-14T02:16:44Z

RPerry:

To ensure clear provenance and authenticity tracking of each deposit, the ADA is basing its workflow in the OAIS model (see R11 for detailed workflow).

Depositors are required to sign an ADA Data License (see R02 Rights Management) confirming ADA has the right to share the data. The original data and metadata a depositor submits to the ADA Deposit Dataverse instance (see R14 Storage and Integrity) is preserved unchanged as a Submission Information Package (SIP) by the ADA Processing Tool (ADAPT). ADAPT is a web-based tool developed by ADA to ensure that data and metadata in the archive are programmatically moved between Dataverse instances and ADA’s archival storage. ADAPT implements PROV-O [3] to express basic classes to log these activities. Any curation required is done on a copy of the data.

The curation and processing of the data are recorded in a processing report supplied to and approved by the depositor, and also programmatically for quantitative data in SPSS or R syntax. These documents are stored under a unique six-digit identification number (ADAID) with the SIP as part of the Archival information package (AIP). See R10 Quality Assurance for details of the curation.

The Dissemination Information package (DIP) is generated from the AIP and is made accessible on separate instances of dataverse, first on the Test Dataverse for the depositor to review, then on the Production Dataverse for user access (see R14 Storage and Integrity).

Changes or updates to the data files of an already published deposit are treated like a new deposit, i.e. a new SIP, AIP and DIP are created. Metadata changes by depositors are managed through the ADA ticketing system, which includes identification checks by ensuring contact information matches the corresponding verified user account on Dataverse.

Once the data is published on the Production Dataverse, any changes to files and metadata are tracked in Dataverse’s versioning with details of any changes accessible to all users.

==References==
[3] PROV-O – (https://www.w3.org/TR/2013/REC-prov-o-20130430/)

[31] Provenance and authenticity – (https://docs.ada.edu.au/index.php/Provenance_and_authenticity)

Expertise & Guidance

2024-09-14T01:57:38Z

RPerry:

== Internal resources ==

The ADA staff bring expertise in quantitative and qualitative data archiving, social science methodology, access management and user experience. ADA staff include experts in technology, digital security, software development and programming. Academic staff at ADA regularly publish in peer reviewed social science and digital humanities journals and are recognised experts in associated fields.

The ADA is situated within POLIS: The Social Policy Research Centre at ANU [17]. This arrangement provides the ADA ready access to a range of academic experts in social policy research, methodology, and data experts in a range of relevant social science fields. The ADA benefits from the advice and contribution of members of the POLIS scientific advisory board [66]. The board members include international and Australian leaders in survey research, with particular expertise in survey design, internet-based surveys, sampling error, and longitudinal research.

Recurrent funding from ANU has supported the continued operation of ADA since 1981 and provides sufficient resources to recruit and train appropriately skilled staff.

ADA maintains an internal wiki to capture and share resources among staff including training and onboarding content. ADA staff regularly undertake professional development including workshops and seminars, conference attendance, and auditing of courses in the POLIS curriculum.

All ADA staff meet twice weekly to discuss any data protection and access issues with the Director. The ANU Research Contracts Office and University Legal Office are available to advise ADA on contracts and intellectual property issues.

Internal expertise and continued funding and resources ensures the ADA can accommodate evolutions in data types, volumes, and rates. The ADA regularly adopts and develops effective new technologies including digital tools for data processing and risk assessment, and data discovery and dissemination.

==External engagement ==

The ADA actively engages with a range of networks, organisations, and activities that provide opportunities for exchanging professional expertise and industry guidance. Current engagements related to social science research infrastructure include:

*Project partner and work package lead on: The WorldFAIR Project (https://worldfair-project.eu/)
*Member organisation with: World Data System (WDS; https://worlddatasystem.org/)
*Steering Group and Expert Group members for the: Academy of the Social Sciences in Australia Decadal plan for social science research infrastructure (https://socialsciences.org.au/news/decadal-plan-for-social-science-research-infrastructure-launches/)
*The ADA host institution is a member organisation with: Australian Research Data Commons (ARDC): https://ardc.edu.au/
*ADA staff are individual members of: International Association of Social Science Information Service and Technology (IASSIST): http://www.iassistdata.org/
*Staff attend and teach into training programs at: Australian Consortium of Social and Political Research (ACSPRI): http://www.acspri.org.au/

==References==
[17] The Centre for Social Policy Research (POLIS) – (https://csrm.cass.anu.edu.au/)

[30] Expertise & Guidance – (https://docs.ada.edu.au/index.php/Expertise_%26_Guidance)

[66] POLIS Scientific Advisory Board – (https://csrm.cass.anu.edu.au/people/advisory-board)

Rights Management

2024-09-14T01:27:50Z

RPerry:

= Rights Management at ADA =

As an overall approach to rights management of deposited files, data, and metadata, the Australian Data Archive (ADA) aims to balance the needs of both data custodians and data users. The ADA works with data custodians to establish a license agreement that includes explicit conditions under which the ADA can disseminate data and other materials to secondary users. The ADA confirms that the depositor holds intellectual property rights over the data, and the agreement with ADA includes that the depositor retains those rights.

The ADA encourages minimal access conditions that still meet requirements for data protection and ensures all prospective users have met those conditions before providing access.

At ADA, rights are primarily managed through the License Agreement and the associated Terms of Use. Using the License Agreement, the data custodians or their representatives provide ADA the right to disseminate their data and other materials under specified conditions. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data.

The rights of ADA to store or preserve the data are implied by the requirements for dissemination of that data.

== License Document Suite ==

When the dataset(s) have been populated with the prepared data files and all of the associated supporting documentation, the next most important activity is the completion by the Data Owner or their authorized representative of the License Document Suite. This consists of three parts:

The License Agreement Form
The License Terms and Conditions of Use
The License Access Guestbook
Each part plays an important role in ensuring that the data deposited with the ADA is managed correctly and that access is granted only to those persons who are deemed to have valid and genuine reasons for accessing the material. The License Document Suite not only helps to establish the access conditions for your data but also records these, and as such, this set of documents will be saved as part of the Submission Information Pack (SIP) in the ADA’s archive.

== License Agreement Form ==

This form, when signed by the copyright holder/Data Owner or their authorized representative, provides the ADA with the authority to both archive the data (as the Submission Information Package) and to redistribute the data on behalf of the Data Owner based upon the satisfaction of certain access criteria. Without a License Agreement Form, a deposit will not be published.

There are a number of specific access types that can be selected for the redistribution of the data; however, where these do not meet the data owner’s requirements for access, Non-Standard Access conditions can be agreed with the ADA Director.

The License Agreement Form should name the project covered by the agreement and list all files that are to be deposited. Where data from multiple projects are to be deposited, a separate License Agreement Form should be completed and signed for each. A separate License Agreement Form may also be required when data files from the same project are to have different access conditions.

The License Agreement Form allows you to assign an Embargo period to your data or a subset of your data. Embargo periods should be for a specific and reasonable amount of time to meet expectations of ADA’s users.

== Copyright ==

It is essential that the depositor of the data is either the data rights owner or their authorized representative and that they hold the copyright or are authorized by the copyright holder to release the material to the ADA for archiving and publication. In most cases, individual researchers have created their own dataset(s) and therefore they, their institution, or the project funder (depending upon arrangements) own the copyright to this information.

The License Agreement Form should be signed by the depositor as an authorized representative of the data rights holder. This signature authorizes the ADA to archive and publish the data. It also confirms the information provided by the depositor is accurate and that the necessary copyright consent and ethics considerations have been met.

== Licensing Statement ==

As the owner of the copyright in the material described in the Schedule of Materials Deposited hereto or duly authorized by the owner of the copyright in the material, I grant to the Australian National University (ANU) a non-exclusive license to publish the data and information contained in the material for the purpose of further analysis and the publication of the results of such analysis subject to the following conditions:

=== 1. Undertakings by Users as set out in the Access Guestbook and Terms and Conditions of Use ===

Any person or institution applying for copies of the data in machine-readable form, codebooks, and/or other documents of assistance to the analysis of the data (with the exception of those described in Section 2 below and Open Access materials described in Section 3.b below) or for analysis of the data to be carried out by the Australian Data Archive (ADA) shall be required by the ADA Director to give undertakings as set out in the Data Owner defined Access Guestbook and Terms and Conditions of Use. The ADA and The ANU accept no responsibility for the consequences of any breach of these undertakings. The undertakings are deemed to be given through the selection of the Request File Access window ‘Request Access’ button and the Download File window ‘Accept’ button within Dataverse. The ADA Director shall act at all times to fully preserve the individual confidentiality of survey respondents and their replies.

=== 2. Publication of Information about Material ===

In order that information about the material deposited in the ADA may be circulated among interested persons or institutions, the ADA Director may (subject to the constraint in Section 1 above) publish questionnaire forms, the text of particular questions, and statistical summaries of answers to particular questions, codebooks, and outline descriptions of the deposited material.

=== 3. Access to Data for Analysis ===

There are two main types of data handled by the ADA: Sensitive and Non-Sensitive. Access to this data is then managed under four standard access categories that Data Owners can select from in this License Agreement. Non-Standard Access conditions can be negotiated with the ADA Director on an ad-hoc basis if required, but these should deviate as little as possible from the standard ADA options offered. It is also possible for some Sensitive datasets to have Non-Sensitive releasable sub-sets or versions. Where required, these can be managed using different access strategies if the Data Owner so chooses. For example, a Data Owner may wish to grant access permissions to the Sensitive data whilst the Non-Sensitive data access could be managed by the ADA with the agreement of the Data Owner.

== Terms and Conditions of Use ==

The Terms and Conditions of Use is the agreement between you, the Data Owner, and End-Users of your data. Users must agree to the terms upon request and before they are granted access to your data.

The Terms and Conditions of Use stipulate compliance failures, including inappropriate use of your data or the failure to keep your data secure once access has been provided. Penalties for non-compliance vary depending upon the nature of the breach and the findings of any investigation. Penalties for non-compliance may include temporary suspensions of access or permanent withdrawal of access to ADA’s holdings for users and possibly their organization. Legal action may be undertaken in serious cases of non-compliance.

To assist in the selection of the correct License Terms and Conditions of Use, the ADA provides the ADA License Terms and Conditions of Use document. This document details the standard Terms and Conditions recommended by ADA for most projects.

If required, a tailored set of Terms can be developed through consultation with the ADA. The Terms and Conditions of Use document includes a section where you can draft Non-Standard terms for review by ADA. Additional fields are available to augment the Terms that you have chosen, and these may be used to set additional conditions without the need to modify the ADA standard terms. Template wording for each additional field is provided.

For Open Access categories of data, the ADA also allows you to select Creative Commons (CC) Terms of Use.

The agreed Terms and Conditions of Use for your data are to be formally confirmed on your License Agreement Form.

== Dataverse Guestbooks ==

As part of your License Agreement with the Australian Data Archive (ADA), you, the Data Owner, require the ADA to store and provide access to your datasets in a responsible manner. Similarly, all users of your dataset are required to accept and adhere to the Terms and Conditions of Use for the material supplied to them. The Terms and Conditions of Use will already have been selected by you, but you may have identified the need for a supplementary request for information about the intended secondary use of the data through the completion of a License Access Guestbook. The License Access Guestbook is a series of questions that will be asked of the user that must be completed prior to the dataset being made available to download or a request for access being submitted.

The ADA Standard Guestbook includes a set of questions that capture basic user demographic information (name, contact email, institution, position) and information about the intended use of the data. This information is mandatory, and access will not be granted without sufficient details being provided by the user. A custom question set can be developed in consultation with the ADA.

Unless specified in the License Agreement Form and identified in this form, a License Access Guestbook will not be applied to your data. When specified, the relevant ADA Standard Access Guestbook question set will be used to collate all user and use information (where required) prior to access being granted to the dataset or prior to the access request being submitted.

In general, approval to download data from ADA Facilitated and Non-Standard Access datasets will only be provided for staff members of research organizations, students conducting higher degrees by research, and for some other authorized research purposes. Therefore, applications to access these datasets will also include a check by ADA staff that the email address provided is an institutional email address. Students will also be required to provide their supervisor’s contact details in order to be approved for download access.

== Business Rules ==

Developed by ADA in consultation with the data custodian, usually via video conference to discuss the license agreement and access conditions.

Rules govern:

Appropriate responses to guestbook questions
Procedures for granting access
The ADA access management team will adhere to the relevant business rules when processing every access request.

== Compliance Details ==

Through consultations, ADA ensures that we are able to meet requirements for managing access and that data owners understand the implications of sharing their data. The access team monitors compliance by ensuring requests meet business rules.

== References==
[26] Rights Management - https://docs.ada.edu.au/index.php/Rights_Management

Mission & Scope

2024-09-14T01:26:57Z

RPerry: /* References */

The Australian Data Archive ([https://ada.edu.au/about-ada/ ADA]) provides a national service for the collection and preservation of digital research data; primarily in the domain of Social Science (Social, Political and Economic affairs), disseminating this data for secondary analysis by academic researchers and other users (ADA Collection Policy Mission Statement) [40].

The ADA is based in POLIS: The Centre for Social Policy Research, in the Research School of Social Sciences [17] at the Australian National University (ANU). ADA was established in 1981 with a mission to provide a national service for the collection and preservation of digital data relating to social, political and economic affairs and to make these data available for further analysis.

The mission statement is approved by the Director of the ADA, in consultation with the Director of POLIS and ADA stakeholders.

==References==
[17] The Centre for Social Policy Research (POLIS): https://csrm.cass.anu.edu.au/

[25] Mission & Scope – (https://docs.ada.edu.au/index.php/Mission_%26_Scope)

[40] ADA website: https://ada.edu.au/about-ada/

Mission & Scope

2024-09-14T01:21:19Z

RPerry:

Security

2024-09-14T01:18:42Z

RPerry:

== Security Levels ==
The four primary ADA Dataverse installations are deployed on NCI VMware servers and are secured and monitored by NCI [7], and ANU ITS and CIO services [52]. Access to the VMs is controlled by NCI – the ADA Technical Manager requests when specific users should be given SSH access, with what privileges, and when they should be removed.

Access to ADA’s NCI-hosted remote desktop service (RDS) is through an NCI-managed GlobalProtect VPN ADA-specific group. The ADA Technical Manager communicates with NCI to request ADA employees be added to and removed from that group as needed when onboarding and offboarding employees.

The Dataverse backend PostgreSQL database ports are locked down to restrict access. NCI and the ADA DevOps manage access to these ports.

The ADA Dataverse installations are protected as much as possible by a conservative f5 WAF [55] that is tuned as needed. Suspicious activity that the WAF catches is blocked, monitored and reported to the ADA technical team. NCI implements an automated weekly scan of ADA services including Dataverse installations and sends a report to the ADA team highlighting potential and real security issues. The ADA DevOps is responsible for addressing those security issues and reporting any that remain unresolved.

The four primary Dataverse installations are protected as much as possible by a conservative f5 WAF [55] that is tuned as needed. Suspicious activity that the WAF can catch is blocked, monitored and reported to the ADA technical team. NCI implements an automated weekly scan of ADA’s services including Dataverse installations and sends a report to the ADA team, plus others, highlighting potential, and real, security issues. The ADA DevOps is responsible for addressing those that are possible to address and reporting back on those that are not. The SIP/AIP/DIP files reside on NCI storage (server). This is protected by NCI standard protocols.

== Security Measures ==
* IT security is implemented by NCI and ANU Information Technology Services (ITS) [52].
* Risk analysis lies with NCI and ITS.
* Risk analysis relative to level of data sensitivity is undertaken by the ADA Archivist team.

According to the Australian Government Security Classification System, data archived at ADA is deemed as UNCLASSIFIED - DLM (dissemination limiting marker). The DLM would be 'Sensitive' or Sensitive-Personal'. - Protective Security Policy Framework [56]. Any data that is deemed too high risk to be made available for download through Dataverse is requested through Dataverse, but the data transfer is completed through an external service AARNET File Sender [57].

== Security for the Facility & Digital Objects Premises ==
IT security and risk analysis is implemented by NCI and ANU Information Technology Services (ITS) [52].

Risk analysis relative to level of data sensitivity is undertaken by the ADA Archivist team. Any data that is deemed too high risk to be made available for download through Dataverse is requested through Dataverse, but the data transfer is completed through an external service – AARNET File Sender [57].

The ADA office is secured and accessible by ANU-issues staff card access for ADA staff only. The access card is an ANU centrally controlled photo identity security system. All secure physical data objects are stored in a locked safe in a locked storeroom, or locked cupboard in a second locked office within ADA. Computer screens are locked while staff are absent from their desks.

NCI servers are protected according to NCI standards. NCI is based in a secure building on ANU campus accessible to authorised NCI staff only. Approved visitors must be signed in, wear visitor identification, and be accompanied by NCI staff.

The ADA complies with ANU policy for Information technology security [58] and Code of Conduct [59].

== Authentication & Authorisation==
Dataverse maintains CoreTrustSeal appropriate application-level security and user authentication [60].

Access to ANU infrastructure is restricted to students or staff members of the ANU. Roles and corresponding system privileges are managed by the ANU ITS team [58].

Access to the NCI infrastructure requires a NCI user account. Users who wish access to NCI infrastructure must apply for an NCI Project to be created. That request is approved or rejected by NCI administrators. The Project owner/manager must grant access to specific NCI user accounts to allow those user accounts access. NCI user accounts are forced to be reasserted and a new password created every 6 months.

Access to data for the ADA archiving team is through the secure NCI RDS set up specifically for ADA. The ADA RDS is behind the NCI f5 firewall where it has direct access to the ADA data storage also managed by NCI. The ADA RDS requires GlobalProtect [61] VPN to login, and to be a member of a specific GlobalProtect group. The ADA Technical Manager requests a new ADA archivist to be added to the group when they begin employment and requests removal when an employee leaves.

== References ==
[58] ANU Policy: Information technology security – (https://policies.anu.edu.au/ppl/document/ANUP_000421)

[59] ANU Policy: Code of Conduct – (https://policies.anu.edu.au/ppl/document/ANUP_000388)

[60] Dataverse Security – (https://dataverse.org/book/security)

[61] Global Protect – (https://www.paloaltonetworks.com.au/sase/globalprotect)[7] National Computational Infrastructure – (https://nci.org.au/)

[52] ANU ITS – (https://services.anu.edu.au/business-units/information-technology-services)

[55] F5 – (https://www.f5.com/)

Technical Infrastructure

2024-09-13T07:32:21Z

RPerry:

== Repository Software ==
The ADA implements the OAIS Reference Model [42] with deployed Dataverse [49] installations for the SIP (deposit.ada.edu.au), AIP (dataverse-test.ada.edu.au) and DIP (dataverse.ada.edu.eu). The Dataverse Project [49] is open source and community-supported code. The Dataverse team has described how the Dataverse software meets CoreTrustSeal Technical Infrastructure requirements [50].

ADA also implements web-based tools, developed and maintained in-house, to support its archiving process:
* Curation and Risk Assessment Tool (CARAT) [73]
* ADA Deposit and Preservation Tool (ADAPT) [6]
* Ingest Reporting Tool (upload of SPSS, generates data dictionary, quality check, confidentiality check) [74]

Access management for data access requests from both dataverse.ada.edu.au and anu-dataverse.ada.edu.au production DIP instances is managed through Osticket [51] ticketing opensource software, with access being Granted or Rejected in Dataverse itself by adding file permissions for approved users. Osticket as a service is required to be available to the same extent as Dataverse to be able to manage access requests.

==Version Control ==
The Harvard Dataverse Project team uses GitHub [54] for its version control system. Any tools or software that ADA produces internally are managed through GitHub.

==IT Service Management ==
Due to its simplicity when compared to the ITIL Service Management framework, the YASM Service Management framework has been initiated by the ADA Technical Manager. As part of this YASM framework, a Service Portfolio has been created, to record and track ADA’s various internal and external services.

At the end of every calendar month, the ADA DevOps role performs updates and maintenance tasks on all of ADA’s services, to keep code and applications up to date. A simple Change Management approach is taken to inform the internal ADA team and external Dataverse users of changes that will be implemented with upcoming Dataverse upgrades. ADA maintains Dataverse installations whose sole purpose is to test changes in new Dataverse releases before pushing the update to ADA’s three primary publicly consumed installations. ADA plans the release schedule of new Dataverse versions in step with the Dataverse Project’s releases. Not all available functionality is desired for ADA so any new functionality is tested and evaluated to determine when to enable it.

NCI performs an automated weekly set of security tests on ADA’s NCI-hosted services. A report with any identified issues is emailed to the ADA technical team and to the ADA Director. The ADA technical team carries out maintenance to address the report-identified issues. ADA services are also monitored by the ANU Chief Information Office (CIO) [52], and ADA receives emails that alert the ADA team to any discovered problems, with a request to address them.

==Infrastructure Standards ==
ANU and NCI [7] have security standards in place to prevent ANU and NCI technical infrastructure from being adversely affected. NCI monitors the primary Dataverse installations with its f5 WAF [55] service.

== Availability, Bandwidth & Connectivity ==
The ADA Dataverse installations are available 24/7. Requests are prioritised and managed within the time capabilities of the ADA Access Management team. Messaging is posted to the ADA’s website and production Dataverse instances to alert users to future ADA shutdowns, to allow users to submit data access requests in a timely manner.

NCI manages network availability and bandwidth for ADA’s NCI-hosted services. NCI also manages its f5 WAF that provides a level of protection for the Dataverse installations.

ANU’s central ITS services [52] manage the domains for each Dataverse installation as well as DNS updates for any services not behind the f5 WAF. ITS is responsible for monitoring the domain registrations, to ensure they are renewed before services become unavailable when a domain registration expires.

NCI manages SSL certificates for ADA’s web-based services and inform the ADA technical team when SSL certificates are about to expire, reissuing them for installing on ADA’s virtual machines (VM).

The ADA technical team has implemented monitors that detect when ADA’s VMs go offline, sending an email to the ADA Director, Technical Manager and DevOps roles. The ADA Devops and Technical Manager work to get the systems back online, consulting with NCI if necessary.

ADA is alerted to planned NCI infrastructure outages. The ADA team posts messaging on the Dataverse installations, and the ADA website, that the systems will be offline on the specified date(s) and time(s).

==Disaster recovery==
Hourly snapshots of ADA’s NCI storage are taken, as well as snapshots/backups of ADA’s Dataverse installations including the Dataverses’ local file storage. Backups of the Dataverse databases are created on their specific VM and stored for 3 months. NCI can restore the ADA project storage from regular backups. If any Dataverse installation has to be re-deployed from a snapshot, the ADA Devops role works in conjunction with NCI to get them back up and running with the most recent snapshot.

NCI is consulted on any issues with SSL certificates and may inform the ADA team to consult ANU ITS. ANU ITS is also consulted on issues relating to the domain.

== Technical Change ==
The Dataverse GitHub repo is monitored for new releases. The ADA staff are also members of the Dataverse User Community [19] and are made aware of new releases via that group as well. Any Dataverse bugs or new features needed by ADA are documented by the ADA Technical Manager on the Dataverse GitHub repo.

Any technical changes relating to Preservation and/or Reuse identified by the Archivist Team are brought up with the ADA Technical Team on an as-needed case-by-case basis. The technical change is discussed and evaluated as to whether it is required and possible to implement. If the ADA technical team can implement the needed change, the team manages it in consultation with the Archivist team. The ADA technical team consults with identified external sources to implement changes where required.

Any Dataverse feature requests for functionality deemed missing according to ADA requirements are created as an issue in the Dataverse GitHub [53] for consideration.

==References==
[50] Dataverse support for CTS – (https://dataverse.org/book/technical-infrastructure)

[51] osTicket – (https://github.com/osTicket/osTicket)

[52] ANU ITS – (https://services.anu.edu.au/business-units/information-technology-services)

[53] Dataverse GitHub – (https://github.com/IQSS/dataverse/issues)

[54] GitHub – (https://github.com)[55] F5 – (https://www.f5.com/)

[42] Open Archival Information System (OAIS) Reference Model – (https://public.ccsds.org/pubs/650x0m2.pdf)

[49] The Dataverse Project – (https://dataverse.org)

[6] ADAPT – (https://docs.ada.edu.au/index.php/ADAPT)

[73] ADA CARAT tool – (https://github.com/ADA-ANU/ADA_Research_Data_Tools/tree/main/ADA_DRAT_v2)

[74] ADA Ingest Reporting Tool – (https://github.com/ADA-ANU/ADA_Research_Data_Tools/tree/main/ADA_reports)

[7] National Computational Infrastructure – (https://nci.org.au/)

[19] Dataverse User Community – (https://groups.google.com/g/dataverse-community?pli=1)

Storage & Integrity

2024-09-13T04:14:12Z

RPerry:

The ADA archival workflow [34] outlines processes to manage the integrity of the data and metadata flow through the Archive. The ADA Workflow and Storage Diagram [47] reflects the distinct deposit, ingest, curation, access, and storage locations for each of the archival phases.

==ADA Archive Training ==
The ADA Archivist team are trained with respect to the OAIS Reference Model and how it is implemented within ADA’s technical architecture:
*Deposited data = SIP
*Ingest (curation, processing, data management, preservation) = AIP
*Access = DIP

The Archivist team members are trained to know where and how the data is stored for each of the SIP, AIP and DIP, and actively contribute to ongoing documentation and development of processes. The archivist team are also trained in accessing and processing the raw Information Packages within ADA’s secure Remote Desktop Service.

The ADA access management team manages access to the DIP (dissemination version). The access management team is trained in processes regarding documented Business Rules that dictate an applicant’s being granted or rejected in their application to access the DIP.

The technical management team follows established informally documented workflows to contact the NCI Helpdesk when any storage-related issues arise.

==Data & Storage Management==
The Dataverse software [49] supports reporting, data management and auditing through user accounts for access, authentication, and permissions; to edit, upload, and download data.

ADA previously developed the ADA Data Processing Tool (ADAPT) [6] based on the OAIS Reference Model [42]. ADAPT enables archivists to programmatically manage movement of data and metadata between Dataverse instances and archival storage to manage data integrity. Each user actioned ADAPT function creates or appends to a log using a standard provenance ontology (PROV-O) [3]. The log is stored as part of the AIP to support auditing of archival activities actioned through ADAPT, if required. ADAPT is moving towards its third version as ADA continues to develop strategies to minimise the risk of manual data and metadata management versus building management into a software application.

Data and metadata are stored with each Dataverse instance, and versioned at publication of a dataset. ADAPT is used to move data and metadata between the Dataverse instances as required at each archival phase.

Dataverse exports metadata in a number of formats. The JSON export format of the DDI metadata also includes Dataverse system metadata such as fixity checks on uploaded data files (checksum MD5). The JSON metadata formats are exported by archivists during the Ingest phase and Publish phase. The JSON export is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data.

The archivist Data Curation Process [34] encapsulates data processing, including superseded and new versions of data, in conjunction with support from Dataverse software versioning control.

==Strategy For Multiple Copies ==

ADA has defined a process for the Archivist team to follow to manage multiple copies of the data corresponding to OAIS:

*SIP: A dataset deposited to ADA via Deposit Dataverse is assigned a unique ADAID. When deposited data is uploaded to Deposit Dataverse, uploading creates a copy in the backend server directory /files/xxxxxx/ on deposit.ada.edu.au (where xxxxxx is the DOI suffix created by Dataverse for the dataset). A copy of the deposited data is also automatically stored in ADA-only project storage (../<ADAID>/original). The files in the Dataverse directory will be the same as the files in the project storage.
*AIP: Dataset metadata and files are copied from deposit.ada.edu.au to dataverse-test.ada.edu.au. Copying to Test Dataverse creates a copy in the backend server directory /files/yyyyyy/ on dataverse-test.ada.edu.au (where yyyyyy is the DOI suffix created by Dataverse for that dataset). A copy of those files is created in the ADA-only project storage (../<ADAID>/processing). The files on dataverse-test and /files/yyyyyy are dynamic while the archivists process these files. Processing syntax and any other documentation is also uploaded to ../<ADAID>/processing.
*DIP: Once AIP processing is complete, Dataset metadata is copied from dataverse-test.ada.edu.au to the Production Dataverse, dataverse.ada.edu.au. Copying the files creates a copy in the backend server /files/zzzzzz directory on dataverse.ada.edu.au (where zzzzzz is the doi suffix created by Dataverse for that dataset). The files on dataverse.ada.edu.au /files/zzzzzz will be exported and copied to the ADA-only project storage top-level directory (../<ADAID>/) for preservation.
*UPDATING PUBLISHED DATA: When data for a dataset that has been published on Production dataverse.ada.edu.au (DIP) is to be updated, a new dataset (no metadata) is created on deposit.ada.edu.au into which the depositor uploads the new datafiles; this creates a copy of the files in the /files/bbbbbb on the Dataverse server. A new directory is created on project storage (../<ADAID>/superseded_<creation_date>) and all files from the previous round deposit, processing and publication are moved into that folder.

The update data is moved using ADAPT from Deposit deposit.ada.edu.au into the /<ADAID>/original and the deposit -> processing -> publish workflow starts again. To process the AIP, the previous files on dataverse-test are replaced with the update deposit files. The new DIP files from /<ADAID>/original are uploaded to the existing dataset on dataverse.ada.edu.au, and that dataset is versioned up to a new major version (x.0). This also places the new files in the /files/zzzzzz directory on the Dataverse server.

Backup copies and snapshots of the data on the ADA-only project storage space are created for disaster recovery.

== Risk Management==
The OAIS model is implemented with data stored for each of the SIP, AIP, DIP ../<ADAID>/ directories, and on the Dataverse backend servers. The archive team are trained to strictly follow documented archive procedures to manage the copies across the directories. The ADA workflow procedures [34] minimises the probability of data copies becoming unsynchronised.

== Deterioration Handling ==
ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on NCI servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media. NCI notifies ADA if there are plans for any necessary upgrades and when those upgrades will take place.

The ADA technical team works with NCI to keep server operating systems updated to supported versions. NCI informs the ADA technical team when a Virtual Machine (VM) operating system (OS) is no longer going to be supported. NCI provisions new VMs when necessary, and the ADA technical team moves Dataverse installations to these new VMs.

== Deletion Processes==
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons. The archiving team retains any records relating to the request for deletion. Data in the DIP state cannot be deleted.

As datasets on Deposit and Test Dataverse are not published, deleting a dataset from Deposit does not create problems with the temporary non-production DOI that is created for it. Simply deleting the dataset would delete everything relating to it including the files stored in the backend server /files/xxxxxxx directory. The DOI would not have to be tombstoned [4] as the DOI prefix is a fake or test prefix, unrelated to ADA’s production DOI prefix. The data stored in the ../<ADAID>/ subdirectories are deleted by the responsible archivist.

If required, the ADA will deaccession (rather than delete) datasets that have been published on the production Dataverse. This results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels (generally only ADA staff). The files remain in the Dataverse server /files/zzzzzz/ directory.

==References==
[3] PROV-O – (https://www.w3.org/TR/2013/REC-prov-o-20130430/)

[4] Datacite Tombstone – (https://support.datacite.org/docs/tombstone-pages)

[49] The Dataverse Project – (https://dataverse.org)

[34] Workflows – (https://docs.ada.edu.au/index.php/Workflows)

[47] ADA OAIS Workflows ADAPT DR Diagram – (https://docs.ada.edu.au/images/f/f4/CTS_2024_ADA%2BNCI_-_RDS%2BStorage_solutions_JM_%28V4%29_2024-09-06_wiki.jpeg)

Reuse

2024-09-12T06:46:52Z

RPerry: /* SUPPORTING REUSE */

=Engagement with designated community =
To ensure that data and metadata continue to be understood and used effectively into the future the ADA liaises regularly with the Designated Community – including data infrastructure and methods experts, data owners and custodians, and end users. The ADA works closely with academic colleagues in POLIS: The Centre for Social Policy Research [17] at the ANU which includes experts in research methods, design and statistical practices as well as social science subject matter experts.

The ADA staff are regularly involved in national and international workshops and conferences. And are active members of several industry groups, for example: the DDI Alliance [18], the Dataverse User Community [19], the Australian Consortium for Social and Political Research Inc. (ACSPRI) [20] and the World Association for Public Opinion Research (WAPOR) [21] for data users. The ADA staff also contribute to ANU teaching and training programs.

The ADA access management team interacts regularly with data users via the ticketing system which functions as a request management platform and helpdesk for general enquiries. The ADA actively supports the establishment of new users in the system, and acts as the first contact for queries about data in the collection and general queries about data management and end-of-life solutions for research project data.

=Supporting reuse =
The ADA publishes all quantitative data files in multiple formats that widely used by the designated community to support reuse:

*.sav (SPSS)
*.sas (SAS)
*.dta (STATA)
*.csv

The ADA requires a minimum level of DDI metadata and uses controlled vocabularies and other standards to ensure data is findable and reusable. Expected metadata includes details about the project, contributors, data collection and cleaning procedures, sampling and weighting, related publications and external resources, and geospatial information. Depositors are also expected to provide supporting documents where applicable, including the survey instrument, data dictionary, code book, data user guide, and technical report.

The ADA archivists actively assess deposits for reuse and include usability recommendations in their data processing report for the depositor. Recommendations can include requests for additional metadata or documentation. The ADA supports updates and revisions to published data, metadata, and documentation (as detailed in R11 Workflows).

=References =

[36] Reuse – (https://docs.ada.edu.au/index.php/Reuse)

[17] The Centre for Social Policy Research (POLIS) – (https://csrm.cass.anu.edu.au/)

[19] Dataverse User Community – (https://groups.google.com/g/dataverse-community?pli=1)

[20] Australian Consortium for Social and Political Research Inc. (ACSPRI) – (https://www.acspri.org.au/)

[21] World Association for Public Opinion Research (WAPOR) – (https://wapor.org/)

[18] Data Documentation Initiative (DDI) – (https://ddialliance.org/)

Reuse

2024-09-12T06:46:25Z

RPerry: /* ENGAGEMENT WITH DESIGNATED COMMUNITY */

=Engagement with designated community =
To ensure that data and metadata continue to be understood and used effectively into the future the ADA liaises regularly with the Designated Community – including data infrastructure and methods experts, data owners and custodians, and end users. The ADA works closely with academic colleagues in POLIS: The Centre for Social Policy Research [17] at the ANU which includes experts in research methods, design and statistical practices as well as social science subject matter experts.

The ADA staff are regularly involved in national and international workshops and conferences. And are active members of several industry groups, for example: the DDI Alliance [18], the Dataverse User Community [19], the Australian Consortium for Social and Political Research Inc. (ACSPRI) [20] and the World Association for Public Opinion Research (WAPOR) [21] for data users. The ADA staff also contribute to ANU teaching and training programs.

The ADA access management team interacts regularly with data users via the ticketing system which functions as a request management platform and helpdesk for general enquiries. The ADA actively supports the establishment of new users in the system, and acts as the first contact for queries about data in the collection and general queries about data management and end-of-life solutions for research project data.

=SUPPORTING REUSE =
The ADA publishes all quantitative data files in multiple formats that widely used by the designated community to support reuse:

*.sav (SPSS)
*.sas (SAS)
*.dta (STATA)
*.csv

The ADA requires a minimum level of DDI metadata and uses controlled vocabularies and other standards to ensure data is findable and reusable. Expected metadata includes details about the project, contributors, data collection and cleaning procedures, sampling and weighting, related publications and external resources, and geospatial information. Depositors are also expected to provide supporting documents where applicable, including the survey instrument, data dictionary, code book, data user guide, and technical report.

The ADA archivists actively assess deposits for reuse and include usability recommendations in their data processing report for the depositor. Recommendations can include requests for additional metadata or documentation. The ADA supports updates and revisions to published data, metadata, and documentation (as detailed in R11 Workflows).

=References =

[36] Reuse – (https://docs.ada.edu.au/index.php/Reuse)

[17] The Centre for Social Policy Research (POLIS) – (https://csrm.cass.anu.edu.au/)

[19] Dataverse User Community – (https://groups.google.com/g/dataverse-community?pli=1)

[20] Australian Consortium for Social and Political Research Inc. (ACSPRI) – (https://www.acspri.org.au/)

[21] World Association for Public Opinion Research (WAPOR) – (https://wapor.org/)

[18] Data Documentation Initiative (DDI) – (https://ddialliance.org/)

Reuse

2024-09-12T06:45:44Z

RPerry:

=ENGAGEMENT WITH DESIGNATED COMMUNITY =
To ensure that data and metadata continue to be understood and used effectively into the future the ADA liaises regularly with the Designated Community – including data infrastructure and methods experts, data owners and custodians, and end users. The ADA works closely with academic colleagues in POLIS: The Centre for Social Policy Research [17] at the ANU which includes experts in research methods, design and statistical practices as well as social science subject matter experts.

The ADA staff are regularly involved in national and international workshops and conferences. And are active members of several industry groups, for example: the DDI Alliance [18], the Dataverse User Community [19], the Australian Consortium for Social and Political Research Inc. (ACSPRI) [20] and the World Association for Public Opinion Research (WAPOR) [21] for data users. The ADA staff also contribute to ANU teaching and training programs.

The ADA access management team interacts regularly with data users via the ticketing system which functions as a request management platform and helpdesk for general enquiries. The ADA actively supports the establishment of new users in the system, and acts as the first contact for queries about data in the collection and general queries about data management and end-of-life solutions for research project data.

=SUPPORTING REUSE =
The ADA publishes all quantitative data files in multiple formats that widely used by the designated community to support reuse:

*.sav (SPSS)
*.sas (SAS)
*.dta (STATA)
*.csv

The ADA requires a minimum level of DDI metadata and uses controlled vocabularies and other standards to ensure data is findable and reusable. Expected metadata includes details about the project, contributors, data collection and cleaning procedures, sampling and weighting, related publications and external resources, and geospatial information. Depositors are also expected to provide supporting documents where applicable, including the survey instrument, data dictionary, code book, data user guide, and technical report.

The ADA archivists actively assess deposits for reuse and include usability recommendations in their data processing report for the depositor. Recommendations can include requests for additional metadata or documentation. The ADA supports updates and revisions to published data, metadata, and documentation (as detailed in R11 Workflows).

=References =

[36] Reuse – (https://docs.ada.edu.au/index.php/Reuse)

[17] The Centre for Social Policy Research (POLIS) – (https://csrm.cass.anu.edu.au/)

[19] Dataverse User Community – (https://groups.google.com/g/dataverse-community?pli=1)

[20] Australian Consortium for Social and Political Research Inc. (ACSPRI) – (https://www.acspri.org.au/)

[21] World Association for Public Opinion Research (WAPOR) – (https://wapor.org/)

[18] Data Documentation Initiative (DDI) – (https://ddialliance.org/)

Discovery and Identification

2024-09-12T03:41:52Z

RPerry: /* References */

The ADA holdings are findable through the Dataverse interface that includes a search function for indexed DDI metadata and facets for narrowing search results [71]. Searchable metadata includes topic classification using Australian and New Zealand Standard Research Classification (ANZSRC) Field of Research codes [11] and keywords based on controlled vocabularies including the Australian Public Affairs Information Service (APAIS) subject index [12].

Dataverse provides a formal data citation for each data collection that is published. ADA mints Digital Object Identifiers (DOI) for each data collection, a service supported by Datacite [72].

ADA data holdings are also searchable through the Research Data Australia (RDA) service [16] which harvests ADA metadata for their catalogue of research data across Australia.

The ADA is a registered research data repository with Re3Data [14].

==References ==

[14] Re3Data – (http://www.re3data.org/repository/r3d100010138)

[16] Australian National Data Service RDA – (https://researchdata.ands.org.au/)

[35] Discovery and Identification – (https://docs.ada.edu.au/index.php/Discovery_and_Identification)

[11] ANZSRC FoR codes – (https://vocabs.ardc.edu.au/viewById/316)

[12] APAIS – (http://vocabularyserver.com/apais/)

[71] Dataverse userguide: finding data – (https://guides.dataverse.org/en/4.0/user/find-use-data.html)

[72] Datacite – (https://datacite.org/)

Discovery and Identification

2024-09-12T03:41:42Z

RPerry:

The ADA holdings are findable through the Dataverse interface that includes a search function for indexed DDI metadata and facets for narrowing search results [71]. Searchable metadata includes topic classification using Australian and New Zealand Standard Research Classification (ANZSRC) Field of Research codes [11] and keywords based on controlled vocabularies including the Australian Public Affairs Information Service (APAIS) subject index [12].

Dataverse provides a formal data citation for each data collection that is published. ADA mints Digital Object Identifiers (DOI) for each data collection, a service supported by Datacite [72].

ADA data holdings are also searchable through the Research Data Australia (RDA) service [16] which harvests ADA metadata for their catalogue of research data across Australia.

The ADA is a registered research data repository with Re3Data [14].

=References =

[14] Re3Data – (http://www.re3data.org/repository/r3d100010138)

[16] Australian National Data Service RDA – (https://researchdata.ands.org.au/)

[35] Discovery and Identification – (https://docs.ada.edu.au/index.php/Discovery_and_Identification)

[11] ANZSRC FoR codes – (https://vocabs.ardc.edu.au/viewById/316)

[12] APAIS – (http://vocabularyserver.com/apais/)

[71] Dataverse userguide: finding data – (https://guides.dataverse.org/en/4.0/user/find-use-data.html)

[72] Datacite – (https://datacite.org/)

Workflows

2024-09-12T00:26:20Z

RPerry:

= Assessment for Suitability of Deposit =

When a prospective depositor has made contact with the ADA, the deposit request is assessed by the director or deputy director of the ADA for suitability (see [[Deposit Appraisal & Collection Policy]]).

= Deposit of Data and Documentation =

The depositing data workflow is documented and available to prospective depositors as a “quick deposit guide” [5].

When a depositor contacts the ADA, the proposed deposit is assessed by the ADA for suitability (see R08 Deposit & Appraisal). Once the deposit has been provisionally accepted, an ADA archivist will set up a deposit shell on the ADA Deposit Dataverse instance. The ADA archival workflow is managed across three separate Dataverse installations. See R14 Storage & Integrity on how and where data is stored.

Depositors are instructed to upload all data and supporting documentation files to their Deposit Dataverse. The ADA archivist will prompt the depositor to complete the DDI metadata fields on the deposit shell. The archivist will correspond with the depositor if further information is needed to create complete documentation for their data (See requirements described in R10 Qualty Assurance).

= Data Processing =
When the deposit shell is created using ADA’s ADAPT tool (described in section R07), each deposit is assigned a unique six-digit ADA Identification (ADAID) number. ADAPT will copy the deposited files to an archive directory identified by the same unique ADAID number as the Submission Information Package (SIP; see R07). Within the SIP, the initial draft deposit remains unchanged so that a complete end-to-end audit trail can be always maintained. The archivists generate a copy of the data to update the SIP material as required. Archival and working dircetories are accessed via a Remote Desktop Service (RDS) that is managed by the NCI (see R14 on Storage and Integrity).

Archivists curate the data and documentation as agreed with the depositor. The level of curation may depend on the type of data (e.g., quantitative or qualitative), the perceived value of the data to the designated community, its sensitivity, or other factors as determined in consultation with the depositor. The archivist will check for disclosure risk and liaise with the depositor about how best to mitigate any risks identified. Data will also be checked for re-usability, including appropriate metadata and consistent mapping to supporting documentation such as data dictionary or user guide. Proposed changes to the data are detailed in a Processing Report sent to the Data Owner’s for approval prior to the changes being made. All agreed changes are recorded in the curation syntax as part of the AIP.

= Review and Publication =
Once all agreed changes to the data and metadata have been made, the archivist will set up a preview on the Test Dataverse instance that reflects the intended final production version of both the metadata and files. Once the data owner/depositor has approved the preview, it is duplicated on the Production Dataverse instance using the ADAPT tool. Here the data is published, searchable, and available for access request. DDI metadata is always publicly accessible, as is all project documentation files (unless depositors have specified otherwise). Data access is typically restricted and can be downloaded subject to data access criteria [8], including at minimum an ADA account with a verified institutional email and sufficient responses to any “guestbook” questions (subject to the ADA License Agreement and Terms of Access; see section R02 for details). Access criteria are recorded on ADA’s internal wiki (not publicly available) for reference by access management staff.

Changes or updates to the data files of an already published deposit are handled via the above deposit and processing workflows. Changes are automatically version controlled in Dataverse. Major changes, that is a change to the data, result in a full versioning (i.e. Version 1.0 becomes Version 2.0), while a minor change such as the addition of metadata results in a sub-versioning (i.e. from Version 1.0 to Version 1.1).

= Preservation =
At publication, preservation versions of the DDI metadata are exported using Dataverse export functionality. The metadata is stored in a preservation sub-directory with that deposit’s ADAID in the archive directory, along with a copy of the published SPSS data file(s) and SPSS syntax. The Preservation Plan [9] outlines how ADA manages long term preservation of data and metadata for reuse.

= Adjusting Workflows, Decision Handling, and Change Management =
The ADA Archive Team meets weekly with the ADA Director to discuss workflows and decisions as required. These meetings are minuted and decisions documented on the ADA internal wiki.

=References =

[34] Workflows – (https://docs.ada.edu.au/index.php/Workflows)

[9] Preservation Plan – (https://docs.ada.edu.au/index.php/Preservation_plan)

[5] Deposit guidelines – (https://docs.ada.edu.au/index.php/Quick_Deposit_Guide)

Preservation plan

2024-09-11T00:35:07Z

RPerry: /* References */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool [70] to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the ADA License Agreement and associated Terms of Use [26]. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The signed and completed license agreement is stored and preserved along with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP stage of the archival workflow can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP package cannot be deleted [37]. For data that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the published collection being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to ADA staff with permission levels equivalent to admin. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==
[43] Studies of Childhood, Education & Youth (SOCEY) – (https://www.socey.net/repository/)

[44] ADA Projects – (https://docs.ada.edu.au/index.php/ADA_Projects)

[45] FAIR Principles – (https://ardc.edu.au/resource/fair-data/)[46] CARE Principles for Indigenous Data Governance – (https://ardc.edu.au/resource/the-care-principles/)

[47] ADA OAIS Workflows ADAPT DR Diagram – (https://docs.ada.edu.au/images/f/f4/CTS_2024_ADA%2BNCI_-_RDS%2BStorage_solutions_JM_%28V4%29_2024-09-06_wiki.jpeg)

[37] Storage & Integrity – (https://docs.ada.edu.au/index.php/Storage_%26_Integrity)[42] Open Archival Information System (OAIS) Reference Model – (https://public.ccsds.org/pubs/650x0m2.pdf)

[48] IBM SPSS – (https://www.ibm.com/spss)[62] Dataverse Project FAIR Principles – (https://scholar.harvard.edu/mercecrosas/presentations/fair-guiding-principles-implementation-dataverse)

[70] ADA Preservation Tool – (https://github.com/ADA-ANU/ADA_Preservation_tool)

Preservation plan

2024-09-11T00:35:00Z

RPerry: /* Future Preservation Formats */

Quality Assurance

2024-09-11T00:16:46Z

RPerry:

= Data and Metadata Assessment =
TThe ADA expects a data deposit to meet quality requirements specified in the ADA deposit guidelines [5]. All deposits are assessed for quality assurance by an ADA archivist. This assessment includes both content and form. On the content side, the archivist will examine the data for presence of direct and indirect identifiers. On the form side, the archivist will confirm unambiguous, clear labels for all variables and run spell checks and basic metadata consistency and completeness checks. The archivist will then propose any corresponding changes to the depositor in a formal report. If the depositor does not agree to changes the ADA archivist deems necessary, a deposit may be rejected (see R08 Deposit & Appraisal). If approved by the depositor, the archivist will implement the agreed changes and generate publication-ready versions of the data. All deposits are subject to data-level curation (see R00 Background, part 5).

Accompanying documentation should be submitted to ensure comprehension of the study and the data. The archivist will liaise with the depositor to ensure all necessary value labels and codes are defined, that DDI-Codebook metadata fields are completed on Dataverse, and that the data is maximally findable and reusable. It is not a requirement that a depositor completes all DDI fields, but it is imperative to meet a minimum requirement for reuse as determined by the ADA. The ADA also encourages depositors to include references for related publications and other digital resources in their project metadata on Dataverse.

= Vocabulary & Classification =
The ADA uses [http://vocabularyserver.com/apais/ APAIS] vocabulary for keywords in the Dataverse catalogue, as well as [http://purl.org/au-research/vocabulary/anzsrc-for/2008/16 ANZSRC FoR] codes for topic classification.

= References =

[5] Deposit guidelines - (https://docs.ada.edu.au/index.php/Quick_Deposit_Guide)

Preservation plan

2024-09-10T23:51:01Z

RPerry: /* References */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the ADA License Agreement and associated Terms of Use [26]. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The signed and completed license agreement is stored and preserved along with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP stage of the archival workflow can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP package cannot be deleted [37]. For data that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the published collection being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to ADA staff with permission levels equivalent to admin. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==
[43] Studies of Childhood, Education & Youth (SOCEY) – (https://www.socey.net/repository/)

[44] ADA Projects – (https://docs.ada.edu.au/index.php/ADA_Projects)

[45] FAIR Principles – (https://ardc.edu.au/resource/fair-data/)[46] CARE Principles for Indigenous Data Governance – (https://ardc.edu.au/resource/the-care-principles/)

[47] ADA OAIS Workflows ADAPT DR Diagram – (https://docs.ada.edu.au/images/f/f4/CTS_2024_ADA%2BNCI_-_RDS%2BStorage_solutions_JM_%28V4%29_2024-09-06_wiki.jpeg)

[37] Storage & Integrity – (https://docs.ada.edu.au/index.php/Storage_%26_Integrity)[42] Open Archival Information System (OAIS) Reference Model – (https://public.ccsds.org/pubs/650x0m2.pdf)

[48] IBM SPSS – (https://www.ibm.com/spss)[62] Dataverse Project FAIR Principles – (https://scholar.harvard.edu/mercecrosas/presentations/fair-guiding-principles-implementation-dataverse)

Preservation plan

2024-09-10T23:50:42Z

RPerry: /* Deleting Data & Metadata */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the ADA License Agreement and associated Terms of Use [26]. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The signed and completed license agreement is stored and preserved along with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP stage of the archival workflow can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP package cannot be deleted [37]. For data that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the published collection being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to ADA staff with permission levels equivalent to admin. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:50:28Z

RPerry: /* Reappraisal of Digital Objects */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the ADA License Agreement and associated Terms of Use [26]. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The signed and completed license agreement is stored and preserved along with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:50:05Z

RPerry: /* Preservation Measures */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the ADA License Agreement and associated Terms of Use [26]. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The signed and completed license agreement is stored and preserved along with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:49:39Z

RPerry: /* Preservation Levels & Retention Periods */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
The ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:49:12Z

RPerry: /* Preservation levels and retention periods */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:49:00Z

RPerry: /* File Formats & Metadata Schemas For Long-Term Preservation */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The ADA collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is tabular quantitative data, with a very small proportion of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation.

====Current Preservation Formats====
*Quantitative: SPSS data (.sav), SPSS syntax (.sps) and the DDI JSON metadata comprise the preservation package.
*Qualitative: ADA holds a small number of datasets with minimal long-term preservation support currently. Qualitative preservation processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be available to the wider community when it is in production. The Preservation Tool exports the data in ASCII (.dat) format, extracts data file structure attributes from the .sav file, and exports the syntax in a format readable by a text editor (.sps). The inclusion of the data file attributes ensures the preservation data is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or other tabular data file formats. Once implemented, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode and ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (DDI-Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The ADA archival workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. DDI compatible metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase of the workflow. Metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation levels and retention periods===

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:45:45Z

RPerry: /* Formal Migration, Bit Level Integrity & Obsolescence Planning */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the NCI [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:45:31Z

RPerry: /* Formal Migration, Bit Level Integrity & Obsolescence Planning */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse instances [47] are provisioned, hosted and backed up on National Computational Infrastructure (NCI) servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:45:11Z

RPerry: /* Objectives */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

Key objects are (a) to ensure ADA has administrative, technical and archival processes in place that archive staff and the Designated Community can understand, and (b) to meet effective requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse [47] instances are provisioned, hosted and backed up on NCI servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37]. Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the National Computational Infrastructure (NCI) [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:44:47Z

RPerry: /* Responsibilities */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing over this time in response to the needs of its Designated Community. The ADA keeps pace with and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles [46] for Indigenous Data Governance, supporting for Indigenous lead projects and research [44], and developing CARE oriented archival practise.

== Objectives ==

To ensure ADA has administrative, technical and archival processes in place that the Archive, depositors, and the Designated Community can understand, and to follow requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse [47] instances are provisioned, hosted and backed up on NCI servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37]. Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the National Computational Infrastructure (NCI) [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:44:26Z

RPerry: /* Scope */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files dating from 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through a funded project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the ADA for all data that it is authorised to share [26] and which is deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing from the needs of its Designated Community. In this time ADA has continued to bring expertise and guidance, situated within POLIS: The Social Policy Research Centre [17] at ANU. This enables ADA to keep pace and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) Principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, and Ethics) [46] by taking opportunities where possible to provide support for Indigenous focussed projects and research [44], with the aim of gaining a deeper understanding of doing CARE oriented archiving.

== Objectives ==

To ensure ADA has administrative, technical and archival processes in place that the Archive, depositors, and the Designated Community can understand, and to follow requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse [47] instances are provisioned, hosted and backed up on NCI servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37]. Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the National Computational Infrastructure (NCI) [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Preservation plan

2024-09-10T23:44:06Z

RPerry: /* Australian Data Archive Preservation Plan */

The plan covers data and metadata managed by the ADA for digital preservation and reuse, based on the Open Archival Information System (OAIS) Reference Model [42]. The plan outlines the scope, responsibilities, objectives, and actions for preserving data deposited with the ADA. It does not cover administrative data or other data related to the function of the ADA.

== Scope ==

ADA holds over 1600 datasets and 13,000 data files through 1833 until the present day, available for reuse through the ADA Dataverse platform [10]. Most data are focussed within the social sciences as quantitative survey data, but ADA has published a small qualitative collection [43] through an ARDC project to develop support for archiving of qualitative data. Ongoing preservation of data is provided by the Archive for all data that is authorised to share [26] and deemed suitable once approved at each step of the archival workflow [34], beginning with the deposit appraisal process [22].

== Responsibilities ==

ADA has been responsible for providing data archival and long-term preservation support since 1981 [25], growing from the needs of its Designated Community. In this time ADA has continued to bring expertise and guidance, situated within POLIS: The Social Policy Research Centre [17] at ANU. This enables ADA to keep pace and meet user requirements within the technical and user landscape, with active participation through external engagement and memberships [30], in-kind collaborations, and funded projects [44]. ADA ensures data is preserved for future usability under the FAIR (Findable, Accessible, Interoperable and Re-Usable) Principles [45] supported through the implementation of FAIR in the Dataverse platform [62]. ADA is actively working towards the realisation of CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, and Ethics) [46] by taking opportunities where possible to provide support for Indigenous focussed projects and research [44], with the aim of gaining a deeper understanding of doing CARE oriented archiving.

== Objectives ==

To ensure ADA has administrative, technical and archival processes in place that the Archive, depositors, and the Designated Community can understand, and to follow requirements for long-term preservation and management of data and metadata.

==Actions==

===Formal Migration, Bit Level Integrity & Obsolescence Planning===
ADA has no present requirement for format migration of data holdings due to the type of data deposited and reused by the Designated Community. ADA Archival Storage and Dataverse [47] instances are provisioned, hosted and backed up on NCI servers. NCI has procedures for monitoring bit level integrity against the deterioration of their storage media [37]. Obsolescence planning, bit level integrity, and storage migration is managed on behalf of ADA by the National Computational Infrastructure (NCI) [7].

===File Formats & Metadata Schemas For Long-Term Preservation===
The Archive’s collection policy [22] outlines preferred data formats suitable for depositing data, and for long-term preservation. Most archived data is statistical quantitative data, with a very small number of qualitative data. IBM SPSS [48] data is currently the most common format used by ADA’s Designated Community, so is at present the format used for long-term preservation. 
Current Preservation Formats:
* Quantitative: SPSS .sav data file, the SPSS syntax (.sps) and the DDI JSON metadata provide the preservation data.
* Qualitative: ADA holds a small number of datasets with no active long-term preservation support currently as the processes are in development.

====Future Preservation Formats ====
ADA has developed an R Preservation Tool to export SPSS data currently preserved as .sav to an ASCII format readable by a text editor. The Tool will be available on ADA GitHub and will be presented to the wider Dataverse community when it is in production. 
Tool preservation functions:
* Exports the data in ASCII format as .dat
* Extracts the data file structure attributes from the .sav file, then exports the syntax in .sps format readable by a text editor.

The inclusion of the data file attributes is readable by a text editor or can be run directly in SPSS to rebuild the .sav, or be used to rebuild the data file in other tabular data file formats.

As part of ADA’s reappraisal process for digital objects, ADA will process all preservation .sav data files to the new preservation format using the R Preservation Tool. The tool is successfully running on the ADA R Shiny server in test mode, ready for implementation.

====Metadata Schemas ====
The Data Documentation Initiative (DDI) [18] metadata schema (Codebook) is the standard metadata schema to describe data collected and used by the Designated Community. DDI is implemented by the Dataverse application.

The Archive workflow [34] procedures ensure there is sufficient documentation collected for long-term usability and reuse [36]. Metadata for each dataset is exported from Dataverse for preservation by archivists during the Ingest phase and Publish phase. The metadata is copied to archival storage for preservation of the original (SIP) metadata and data files, and the published (DIP) metadata and data files, to ensure that the integrity of digital objects from deposit to access can be verified against any changes to the data [37].

===Preservation Levels & Retention Periods===
ADA has one standard level of preservation and retention for all datasets approved for deposit. Approval is managed through the ADA deposit appraisal process [22], continuing through the archival workflow [34].

===Preservation Measures===
Rights to preserve and disseminate data are primarily managed through the License Agreement and the associated Terms of Use. Data users agree to abide by these conditions when they indicate their agreement with the Terms of Use upon requesting access to the data [26]. Completion of the license is part of the deposit appraisal process [22] to ensure appropriate metadata is collected to support future reuse [36]. The license agreement (PDF) is stored and preserved with the Archival Information Package (AIP).

===Reappraisal of Digital Objects===
Reappraisal of digital objects is driven by requirements in the Designated Community, or by technological, or policy changes within or external to ADA. Changes to curation or preservation levels of digital objects are identified and managed through the formal weekly archivist team meetings, including regular participation by the ADA Director, and the ADA Technical Manager as needed [34]. The formal structure of the weekly meetings ensures outcomes are considered from archival, organisational, and technical perspectives.

===Deleting Data & Metadata===
Data in the SIP or AIP state can be deleted by the ADA archivist team if directed by depositors, or for legal reasons, with the archiving team maintaining records relating to the request for deletion. Data in the DIP state cannot be deleted [37].

For datasets that have been published on ADA’s production Dataverse [10], ADA does not delete them but rather deaccessions them. This process results in the dataset being labelled as “Deaccessioned” in Dataverse and renders its files accessible only to users with the correct permission levels. There is no need to tombstone [4] the DOI as the dataset landing page is still available.

==References==

Expertise & Guidance

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Expertise & Guidance

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=Expertise and Guidance=

== Internal resources ==

The ADA staff bring expertise in quantitative and qualitative data archiving, social science methodology, access management and user experience. ADA staff include experts in technology, digital security, software development and programming. Academic staff at ADA regularly publish in peer reviewed social science and digital humanities journals and are recognised experts in associated fields.

The ADA is situated within POLIS: The Social Policy Research Centre at ANU [17]. This arrangement provides the ADA ready access to a range of academic experts in social policy research, methodology, and data experts in a range of relevant social science fields. The ADA benefits from the advice and contribution of members of the POLIS scientific advisory board [66]. The board members include international and Australian leaders in survey research, with particular expertise in survey design, internet-based surveys, sampling error, and longitudinal research.

Recurrent funding from ANU has supported the continued operation of ADA since 1981 and provides sufficient resources to recruit and train appropriately skilled staff.

ADA maintains an internal wiki to capture and share resources among staff including training and onboarding content. ADA staff regularly undertake professional development including workshops and seminars, conference attendance, and auditing of courses in the POLIS curriculum.

All ADA staff meet twice weekly to discuss any data protection and access issues with the Director. The ANU Research Contracts Office and University Legal Office are available to advise ADA on contracts and intellectual property issues.

Internal expertise and continued funding and resources ensures the ADA can accommodate evolutions in data types, volumes, and rates. The ADA regularly adopts and develops effective new technologies including digital tools for data processing and risk assessment, and data discovery and dissemination.

==External engagement ==

The ADA actively engages with a range of networks, organisations, and activities that provide opportunities for exchanging professional expertise and industry guidance. Current engagements related to social science research infrastructure include:

*Project partner and work package lead on: The WorldFAIR Project (https://worldfair-project.eu/)
*Member organisation with: World Data System (WDS; https://worlddatasystem.org/)
*Steering Group and Expert Group members for the: Academy of the Social Sciences in Australia Decadal plan for social science research infrastructure (https://socialsciences.org.au/news/decadal-plan-for-social-science-research-infrastructure-launches/)
*The ADA host institution is a member organisation with: Australian Research Data Commons (ARDC): https://ardc.edu.au/
*ADA staff are individual members of: International Association of Social Science Information Service and Technology (IASSIST): http://www.iassistdata.org/
*Staff attend and teach into training programs at: Australian Consortium of Social and Political Research (ACSPRI): http://www.acspri.org.au/

Governance & Resources

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= Organisation of the ADA =
The ADA staff comprises 9 staff members at time of submission, with a total of 7.55 FTE:

*Director
*Technical Manager
*Archive Manager
*Researcher
*Software developer
*Senior data access officer
*Data access officer (part time)
*Data archivist (x2)

ADA staff are organised into three groups within the archive – Data Access, Data Archiving, and Technical.

The ADA director reports to the Director of POLIS: The Centre for Social Policy Research [17] at ANU. The ADA sits within POLIS. As part of an established ANU Centre, ADA is governed by the ANU Policy on Centres and Institutes [41].

In addition to ADA staff, additional IT functions are provided by external partners:

*The National Computational Infrastructure (NCI) [7] is Australia’s preeminent computing facility, delivering on the critical national need for high-performance data, storage, and computing services. NCI provides compute, storage and network infrastructure for the ADA, and is supported by a team of over 70 staff, funded through Australia’s National Collaborative Research Infrastructure Strategy (NCRIS) [67].
*The Australian Consortium for Social and Political Research Incorporated (ACSPRI) [20] provides development operations support for the ADA on a contractual basis. ACSPRI and ADA have a long-term collaboration dating back to the establishment of both organisations in 1981.

= Operational Costs and Recruitment =
The ADA is funded on an ongoing basis by the Australian National University (ANU), primarily through the National Institutes Grant [68] provided directly to the ANU by the Australian Federal Government. This funding has been supporting ANU since its establishment in 1981. This core funding is supplemented by project grant funding from a variety of sources. In the last 10 years, this has included funding through the Australian Research Council, Australian Research Data Commons, Horizon Europe (European Commission) and contract research with government agencies and other external partners.

= Recognised host institution =
The ADA is hosted by the Australian National University (ANU) and housed organisationally within POLIS: The Social Policy Research Centre in the Research School of Social Sciences (RSSS) at ANU.

The Australian National University was established in 1946 through an Act of the Australian Federal Government and continues to be governed by the parliament under the auspices of the Australian National University Act 1991 and the Public Governance, Performance & Accountability Act 2013 [69]. The Australian Data Archive was established within the Research School of Social Sciences in 1981 and has continued to be part of the RSSS since its establishment.

Staffing and infrastructure support for the ADA has enabled the operation of the archive for over 40 years. The continuing operations of the archive will continue to focus on including a breadth of funding sources to supplement the ANU core funding, and use of outsourcing partners to support core archive staff to provide relevant operational functions. As ADA’s budget is part of the overall ANU corporate budget, there is no separate documentation of the ADA’s budget that can be provided. However, while no funding is certain, we expect this strategy to continue providing a sound basis for ADA operations into the foreseeable future.

=References=

[69] ANU Governance – (https://www.anu.edu.au/about/governance)

[17] The Centre for Social Policy Research (POLIS) – (https://csrm.cass.anu.edu.au/)

[7] National Computational Infrastructure – (https://nci.org.au/)

[67] National Collaborative Research Infrastructure Strategy (NCRIS) – (https://www.education.gov.au/ncris)

[68] ANU National Institutes Grant policy – (https://policies.anu.edu.au/ppl/document/ANUP_018016)

[41] ANU Policy on Centres and Institutes – (https://policies.anu.edu.au/ppl/document/ANUP_012009)

Governance & Resources

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RPerry: /* Recognised host institution */

Governance & Resources

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RPerry: /* Demonstrate that the repository can meet its obligations */

Governance & Resources

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RPerry: /* Timescale */

= Organisation of the ADA =
The ADA staff comprises 9 staff members at time of submission, with a total of 7.55 FTE:

*Director
*Technical Manager
*Archive Manager
*Researcher
*Software developer
*Senior data access officer
*Data access officer (part time)
*Data archivist (x2)

ADA staff are organised into three groups within the archive – Data Access, Data Archiving, and Technical.

The ADA director reports to the Director of POLIS: The Centre for Social Policy Research [17] at ANU. The ADA sits within POLIS. As part of an established ANU Centre, ADA is governed by the ANU Policy on Centres and Institutes [41].

In addition to ADA staff, additional IT functions are provided by external partners:

*The National Computational Infrastructure (NCI) [7] is Australia’s preeminent computing facility, delivering on the critical national need for high-performance data, storage, and computing services. NCI provides compute, storage and network infrastructure for the ADA, and is supported by a team of over 70 staff, funded through Australia’s National Collaborative Research Infrastructure Strategy (NCRIS) [67].
*The Australian Consortium for Social and Political Research Incorporated (ACSPRI) [20] provides development operations support for the ADA on a contractual basis. ACSPRI and ADA have a long-term collaboration dating back to the establishment of both organisations in 1981.

= Operational Costs and Recruitment =
The ADA is funded on an ongoing basis by the Australian National University (ANU), primarily through the National Institutes Grant [68] provided directly to the ANU by the Australian Federal Government. This funding has been supporting ANU since its establishment in 1981. This core funding is supplemented by project grant funding from a variety of sources. In the last 10 years, this has included funding through the Australian Research Council, Australian Research Data Commons, Horizon Europe (European Commission) and contract research with government agencies and other external partners.

= Demonstrate that the repository can meet its obligations =
ADA’s staffing and infrastructure support has enabled the operation of the archive for over 40 years. The continuing operations of the archive will continue to focus on including a breadth of funding sources to supplement the ANU core funding, and use of outsourcing partners to support core archive staff to provide relevant operational functions. As ADA’s budget is part of the overall ANU corporate budget, there is no separate documentation of the ADA’s budget that can be provided. However, while no funding is ever certain, it is our expectation that this strategy will continue to provide a sound basis for ADA operations into the foreseeable future, based on our 40 years of continuous operation.