During FAIR review, an RDM expert of the university library's Digital Competence Centre helps you to make your collection more FAIR (Findable, Accessible, Interoperable, and Reusable). This increases the impact of your research and helps to protect the privacy of your research participants. How you can request FAIR review is explained on the helppage Publishing a DSC. The current page shows the topics that are reviewed during the FAIR review.
The FAIR reviewer aims to provide feedback on your collection within five business days after you submitted the collection for FAIR review. If they suggest improvements, it usually requires several additional days to apply these changes in consultation with the reviewer. Thus, the better you prepare your collection before submitting it, the less time the FAIR review process will take.
As described in the RDR Repository Policy the collection manager is responsible for the legal and ethical implications of sharing research data and the correctness of the published (meta)data. The FAIR reviewer does not take over any of these responsibilities. FAIR review serves as an advisory step to improve the quality of individual collections and the RDR as a whole.
The FAIR review topics
The FAIR reviewer will look at the following aspects of your collection, so make sure that they are in order before requesting FAIR review.
Metadata
The title contains the essential elements of the research theme and/or topic of the research data that can be found in the collection. Avoid a title that is vague, short, excessively abbreviated, or so complex that it becomes uninformative.
The description of the collection contains a summary of the context in which the data was collected/created and refers in general terms to the content of the collection. Mention the following in the description:
- The context, i.e. topic of the research (project);
- The method(s) used to collect/create the collection's data;
- General information about the content of the data collection. Refer to the types of data that are present in the collection. This can be done in general and concise wording, but needs to be informative. For example, 'questionnaire data', 'analyses scripts', 'machine output', 'figures used for…', 'research protocols', etc..
The keywords represent the essential elements of the research theme and the data present in the collection. Relevant associated materials (i.e. publications, data, analyses tools and pre-registrations) are added as metadata and have a working link or persistent identifier.
Documentation
The collection contains documentation that informs the user of the content and structure of the collection. This means that it should be clear what type of data or information is present in each folder, subfolder, and file. Usually, documentation is present in a README.txt file in the top folder of the collection.
If the collection contains documentation files in (a) subfolder(s) or if the collection contains embedded documentation, the main documentation should refer to these files and their location. Variables and/or concepts must be explained. This explanation includes:
- Variable/concept name as presented in the data file(s), e.g. “T1_S2_RT”;
- Explanation of that variable/concept, e.g. “Reaction time of participant on stimulus number 2 during study 1”;
- Measurement units (if applicable), e.g. “milliseconds” or “Likert scale 1-7, ranging from…”.
If files are related to each other or need to be used in a specific order, this must be mentioned in the documentation.
File and folder names are concise, consistent, and inform about their content. Concise means that the names do not contain information that is already present in a more logical location (e.g. the metadata) or that does not provide any clarification on the file's or folder's content. Consistent means that a single naming strategy is used for all folders and files. Inform about their content means that folder names inform the user about the shared topic of all subfolders and files; and that file names inform the user about the type of information in the file.
The files and folders are organised in a clear and consistent manner. The structure of the (sub)folders is either clear on first glance or is explained in the main documentation file.
The provided documentation files are “flagged” as documentation files so that they become publicly accessible upon publication of the collection. See this page for how to flag documentation files.
For more information about documentation, see the Radboud university page on documenting data.
Personal data
This check is performed only if the collection manager indicated that there might be personal data in the collection.
There is no personal data present in the metadata, documentation files, folder- and file names, nor the files themselves that you are not allowed to make public. All metadata, documentation files, and folder- and filenames are checked for personal data. A random selection of the files is opened and checked for the presence of personal data. The collection manager remains responsible for the legal and ethical implications of sharing research data, so make sure that you do not share personal data that you are not allowed to share.
For more information about personal data in research, see the Radboud university page on personal data.
Accessibility and reuse conditions
The files are in a preferred file format or the collection manager provided a valid reason to use another format. See our preferred file formats page for more information.
The chosen access level is consistent with the RDR help page. Deviations from the RDR help page can occur, but only after correspondence with the FAIR reviewer and/or a local privacy officer or coordinator. Note that the responsibility for the chosen access level remains with the collection manager. Relevant pages are Selecting a DUA or licence and the Radboud university page on personal data.