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FAIRness and Usability for Open-Access Omics Data SystemsOmics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems.
Document ID
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Berrios, Daniel C.
(Universities Space Research Association (USRA) Moffett Field, CA, United States)
Beheshti, Afshin
(Wyle Labs., Inc. Moffett Field, CA, United States)
Costes, Sylvain V.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
November 7, 2018
Publication Date
November 3, 2018
Subject Category
Documentation And Information Science
Aerospace Medicine
Report/Patent Number
Meeting Information
Meeting: AMIA 2018 Annual Symposium
Location: San Francisco, CA
Country: United States
Start Date: November 3, 2018
End Date: November 7, 2018
Sponsors: American Medical Informatics Association
Funding Number(s)
Distribution Limits
Public Use Permitted.
Technical Review
NASA Peer Committee
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