File & Folder Naming Conventions

It is important that each version of the data and its supporting documentation is clearly identified using the correct file naming convention. This helps to prevent erroneous access conditions from being applied to the published data, and potentially unauthorised access to the material. All data files and supporting documentation that is to be uploaded to Dataverse should therefore be named in accordance with the ADA guidance, this also makes the files easily identifiable to ADA Staff and standardises the naming convention across datasets and Dataverse’s.

Dataverse Uploads

All data and their supporting documentation should be simple to locate and identify. Dataverse automatically lists uploaded files in numerical and alphabetical order. Therefore, in order to list materials in a more meaningful order, the ADA have developed a standardised naming convention for files.

ADA Standard Naming Convention

The ADA standardised naming convention for Self-Deposit files uses the following format:

DataverseNumber_StudyName_Year_StudyArtefact_ADAID note that the Dataverse application will include a file extension to the name during the upload process.

Dataverse Number:

The number 0, 1, 2 or 3, indicating the order that the files are to be arranged in.

- “0” is to be applied to all licensing information files (e.g. License Agreement Forms, License Terms and Conditions of Use, License Access Guestbook’s).

- “1” is applied to all other supporting document files (e.g. Questionnaires, Codebooks, Technical documents).

- Individual zipped and password protected encrypted Data files (e.g. SPSS, Stata, SAS, CSV and Excel) are to be labelled with the prefix “2”.

- Files that are uploaded for ARCHIVING ONLY as part of the Submission Information Pack (SIP), and which are not to be included as part of the published dataset are to be labelled with a "3".

Due to compatibility issues with Dataverse, all individual data files and any supporting files that are in the following formats must be zipped and encrypted with a password prior to uploading to the dataset to preserve their formatting.

- SPSS

- SAS

- Stata

- CSV

- Excel

Folders containing multiple files

In certain cases, a complete zipped and password protected encrypted folder of supporting documentation or data files may be produced (e.g. many longitudinal studies will have multiple files and it would be time consuming to zip and encrypt each file and upload them individually). Where packages of such files are to be uploaded as a single folder, the folder should be annotated with ‘-Z’ immediately following the Dataverse Number. For example a zipped and password encrypted collection of supporting documents that contains files that would require zipping if uploaded individually, when uploaded as a folder would be identified with ‘1-Z’.

The files within the folder should all still be individually named using the standard naming convention detailed in this section. Since all individual data files are required to be zipped and encrypted with a password, there is no need to identify these separately with a ‘-Z’, the -Z should be used purely to identify packages of files uploaded as a zipped and password protected folder.

Where a large number of Supporting Documents (i.e. greater than 40-50) are to be uploaded together as a folder, as long as the files within the folder would not require zipping and password protected encryption if they were uploaded individually (i.e. the folder is a package of supporting documentation files that do not contain data or identifiers, and they are not SPSS, SAS, Stata, CSV or Excel file formats), then the folder need not be zipped or secured with password protected encryption. For example, the License Document suite of forms could be uploaded directly as a older, with no zipping or encryption required.

Files or Folders containing Sensitive or Personal Information

The suffix ‘-S’ is to be used to identify data files that contain Sensitive Information or Personal Information. Typically this is used to differentiate between those data files that may be available for public release as Open Data and those that contain some form of information that requires access to be managed. Many Data Owners will choose to upload both an open source version of their data as well as a version of the data that requires some form of access restriction. The former is most likely to have far fewer safeguards when sharing, and therefore requires less management and maximises the potential benefits of the data for sharing.

Data Files used to create a Derived Dataset

Finally, for derived datasets (i.e. those made up from multiple sources of separate data), the suffix's ‘a’ through ‘z’, should be used to identify the individual data used in the creation of the derived data. Thus if a new data file was created through the linking of data from the ATO and Medicare, the ATO data may have the Dataverse Number ‘2a’ whilst the Medicare data may have the identifier ‘2b-S’, the latter denoting that the data is also Sensitive.

0. Licensing Information files (License Agreement Form, License Terms and Conditions of Use, License Access Guestbook)

1. Supporting Documentation (Questionnaires, Codebooks, Technical documents etc... remember to zip and encrypt those files with SPSS, Stat, SAS, CSV and Excel file extensions)

2. Data files (all are to be zipped and encrypted with a password prior to upload)

2a. Data file used in creation of a derived data file (all are to be zipped and encrypted with a password prior to upload)

3. Files uploaded for archiving with the ADA only (for example Signed Consent forms that are not to be published as part of the dataset but are submitted to complete the deposit and to retain a full audit trail)

-S. The ‘S’ suffix when displayed after the number is used to denote that the Data file contains ‘Sensitive’ data

-Z. The ‘Z’ suffix when displayed after the number is used to denote that multiple files are contained in a zipped folder

By way of example, the Dataverse Number ‘2-SZ’ would denote a zipped package of data files, which contain sensitive data.

Study Name:

This relates to the name of the Project or Study that the dataset(s) belong to. If the full name is unreasonably long this can be abbreviated. For example, ‘The Australian Longitudinal Study on Women’s Health’ is abbreviated to ‘ALSWH’. Where the Study Name is more than a single word, you can either leave the space between words or use an underscore to separate the words. Either is accepted in Dataverse.

Year:

Refers to the year that the Project or Study was conducted in. If this spans multiple years you can enter the period in question. For example, 2018-19.

Study Artefact:

This should refer to the specific item in question. For supporting documentation it could be the item (e.g. Questionnaire, Codebook or Report), for data this is typically the file type (e.g. SAS, SPSS or Stata Data File). Where the Study Artefact is more than a single word, for example: Plain Language Statement, you can either leave the space between words or use an underscore to separate the words. Either is accepted in Dataverse.

ADAID:

This refers to the five digit ADA Identification number assigned to the Project or Study. For Self-Deposits it is unlikely that this number will have been allocated, although it may have been provided by the ADA Archivist when the ‘Shell Dataverse and dataset(s)’ were created. In the event that it has not been provided, use ‘ADAID’ and the ADA Archivist will enter the correct identification details once you have uploaded the file to the dataset.

File Extension:

A file extension (e.g. .pdf, .zip and .xlsx) must be present for every file contained and listed within a dataset. This will be automatically added by Dataverse during the upload process and should not be added by the Data Owner.

Correctly named folder example:

A full example of a correct file name, adhering to the above naming conventions where the ADAID is known is: ‘1_ANUPoll_2018_Questionnaire_01212.pdf’.

Where the ADAID is unknown and the Study Artefact is multiple words, a correct file name would be: '2_ANUPoll_2018_Data_File_Number_1_ADAID.CSV'