=Paper=
{{Paper
|id=Vol-2042/paper18
|storemode=property
|title=Assessment of FAIRness of Open Data Sources in Life Sciences
|pdfUrl=https://ceur-ws.org/Vol-2042/paper18.pdf
|volume=Vol-2042
|authors=Filip Pattyn,Bírínice Wulbrecht,Kenny Knecht,Hans Constandt
|dblpUrl=https://dblp.org/rec/conf/swat4ls/PattynWKC17
}}
==Assessment of FAIRness of Open Data Sources in Life Sciences==
<pdf width="1500px">https://ceur-ws.org/Vol-2042/paper18.pdf</pdf>
<pre>
Assessment of FAIRness of open data sources in life
                   sciences

 Filip Pattyn1[0000-0003-0858-6651], Bérénice Wulbrecht1[0000-0002-9444-1709], Kenny
        Knecht1[0000-0002-1049-3684] and Hans Constandt1[0000-0003-0858-6651]
     1
         ONTOFORCE NV, Ottergemsesteenweg-Zuid 808, 9000 Gent, Belgium
                   filip.pattyn@ontoforce.com



 Abstract. 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.


 Keywords: FAIR data, Linked Data, Data Quality.

</pre>