Ensuring Data Objects Achieve FAIRness
To Achieve FAIRness, Data Objects Should at Least Have:
(CESSDA Training Team, 2020)
- A persistent Identifier (PID)
- A sufficient set of metadata
- A clear license
- If shared, sharing should be done using a data repository
Persistent Identifier
A persistent identifier (PID) for the data object as a whole (see ‘Data citation’). Examples of common PIDs used in research are ORCID identifier (iD) and Digital object identifiers (DOIs). You can join DataCite if you want to register DOIs and use their services. See https://datacite.org/assets/DataCite_Brochure.pdf. In addition, see this link to create your ORCID iD.
Sufficient Set of Metadata
A sufficient set of metadata (see ‘Documentation and metadata’). The term ‘documentation’ refers to all of the data and information required to interpret, comprehend, and use a dataset or a set of documents. Examples of documentation include title, description, creator, funder, keywords, and affiliation.
The following are some examples of embedded documentation:
- Code, field and label descriptions
- Descriptive headers or summaries
- Recording information in the Document Properties function of a file (Microsoft)
Clear Licence
A clear licence (see ‘Data licensing’). If you are not sure what license to apply to your work, see this link for help. The best way to decide which Creative Commons License is appropriate for you is to think about why you want to share your data, and how you hope others will use that data. For help, try the Creative Commons License Chooser.
Data Should Be Shared Using a Data Repository
To be made open and FAIR, data should be deposited in a data repository. Using a data repository is preferable to sharing data as supplementary files alongside a published article, or via cloud-based file storage (such as Dropbox), or maintaining data in private storage and sharing on upon request only. However, these ways of sharing data are not fully FAIR.
A data repository performs a number of specific FAIR functions:
- It actively preserves data for long-term viability.
- It publishes machine-readable metadata to enable online discovery;
- It assigns persistent unique identifiers (e.g. DOIs) to datasets and makes them citable;
- It enhances metadata.
- It manages online access to data so that they can be used by other people.
- It applies licence notices, to make terms of use and attribution requirements clear (Open and FAIR Data, n.d.). Examples of data repositories are presented in Table 1 (below).
Table 1: Examples of Data Repositories
| General-Purpose Data Sharing Repositories | |
| Figshare | It is an online open access repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos. |
| Dryad Digital Repository | It is committed to making data available for research and educational reuse. |
| Zenodo | It is a general-purpose open-access repository. |
| Open Science Framework | It is a free, open-source web application that connects and supports the research workflow, enabling scientists to increase the efficiency and effectiveness of their research. |
| Disciplinary Data Centre and Its Component Database | |
| European Bioinformatics Institute | It makes the world’s public biological data freely available to the scientific community via different services and tools. |