The NFU prescribes that data stewardship at the Dutch UMCs should adhere to the FAIR Principles and comply with HANDS.
The FAIR Principles recommend that all research data should be Findable, Accessible, Interoperable and Reusable, for both machines and people:
- Findable: The data should be uniquely and persistently identifiable and other researchers should be able to find your data.
- Accessible: The conditions under which the data can be used should be clear to machines and humans.
- Interoperable: Interoperability is the ability of data or tools from non-cooperating resources to integrate or work together with minimal effort. Data should be machine-readable and use terminologies, vocabularies or ontologies that are commonly used in the field;
- Reusable: Data should be compliant with the above and sufficiently well-described with metadata and provenance information so that the data sources can be linked or integrated with other data sources and enable proper citation.
Frequently Asked Questions
What does FAIR mean in layman’s terms?
To explain the F and A of FAIR, one can draw a comparison with the worldwide web. People from all over the world can generate websites. You can find and access these websites using a browser. So, the internet makes data Findable and Accessible. Similarly, UMCs can load their research data to secure internet sites, making the data findable and accessible to researchers at other hospitals.
However, the information on a website can have any format. For instance, the language may be Italian or Chinese, or people may use synonyms. This also applies to clinical data sets. For cancer of the larynx, doctors in Leiden may use ‘larynxcarcinoom’, whereas doctors in Maastricht may use ‘strottenhoofdkanker’. To make sure that the data relate to the same disease, we can use a medical ontology such as the ‘international classification of diseases’ (ICD). In the ICD version 11, cancer of the larynx has received the code 2C23. If we use this code when uploading data from patients with ‘larynxcarcinoom’ in Leiden and ‘strottenhoofdkanker’ in Maastricht, suddenly a non-Dutch speaking scientist and even a computer can understand that the patients on the secure internet site have larynx cancer. This is a crucial step to achieve data interoperability and reusability (The I and R of FAIR).
How can I train myself in FAIR data stewardship?
HANDS’ toolbox contains an overview of data-related courses.
How FAIR is FAIR enough?
A minimal step towards FAIRness is to provide the data set, as an entity in its own right, with a PID that is not only intrinsically persistent, but also persistently linked to the data set (research object) it identifies. However, without machine-readable metadata it will still be difficult to find the data, unless one knows the PID. So a PID is necessary, but not sufficient.
- The FAIR Guiding Principles for scientific data management and stewardship;
- Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud (follow-up paper about the FAIR principles);
- A design framework and exemplar metrics for FAIRness;
- Overview of FAIR papers and publications on the GO FAIR website; x
- Guidelines on FAIR Data Management in Horizon 2020;
- GO FAIR - FAIR Principles: fosters the coherent development of the global Internet of FAIR Data & Services, focusing on early developments in the European Open Science Cloud, EOSC;
- Dutch Techcentre for Life Sciences: organises activities around FAIR data.