FAIR Data tools
In the FAIR Data approach data should be:
- Findable – Easy to find by both humans and computer systems and based on mandatory description of the metadata that allow the discovery of interesting datasets;
- Accessible – Stored for long term such that they can be easily accessed and/or downloaded with well-defined license and access conditions (Open Access when possible), whether at the level of metadata, or at the level of the actual data content;
- Interoperable – Ready to be combined with other datasets by humans as well as computer systems;
- Reusable – Ready to be used for future research and to be processed further using computational methods.
An important step in the FAIR Data approach is to publish existing and new datasets in a broadly applicable language and interoperable format that can be understood by computer systems. By semantically annotating data items and metadata, we can use computer systems to (semi) automatically combine different data sources, resulting in richer knowledge discovery activities.
In the effort to make data Findable, Accessible, Interoperable and Reusable (FAIR), the FAIR Data engineering team coordinated by the Dutch Techcentre for Life Sciences has been developing a number of software solutions.
We will demonstrate the FAIR Data Point, a server solution for data owners to make metadata and data available in a FAIR manner. The attendees will have the opportunity to interact with two solutions based on the FAIR Data Point technology. One solution is the FAIR Data Demonstrator, which retrieves metadata and data form a number of FAIR Data Points and provides to the end user (researcher) a simple and intuitive interface to get information about biobanks and patient registries. The other solution is the myFAIR analysis project , a generic “end to end” FAIR data point generator and analysis application for research scientists, built on B2DROP and Galaxy services. The output from myFAIR analysis is location of the input data, the provenance of the workflow and the results of the analysis in a single webpage.