Assessment of FAIRness of open data sources in life sciences
Poster sessions are particularly prominent at academic conferences. Posters are usually one frame of a powerpoint (or similar) presentation and are represented at full resolution to make them zoomable.
The life sciences domain heavily relies on the availability and usabil- ity of open data. Some of these sources are very extensive and are considered as key or golden sources for one type of information in the field. Despite ongoing data structuring, data standardization and data linking efforts, many of these da- ta sources aren’t by default easily usable for integrated analyses in automated workflows. The FAIR (Findable Accessible Interoperable and Reusable) data principles can be used as a guideline to overcome this. There’s currently no re- pository storing information about how FAIR a data source currently is. An as- sessment of the FAIRness of the most used life sciences related open data sources could delineate what the status is of the usability of open data in the field. We analyzed the FAIRness of the largest and most used data sources available in the linked data search and navigation platform DISQOVER and we calculated what the effort is to convert these sources to make them FAIR enough to integrate them in the semantic web based DISQOVER platform. The results show that it requires still a lot of work to upgrade these popular data sources to a higher level of FAIRness.