Manual FAIR Assessments of the AGR and GTEx Web Resources¶
Authors: Megan Wojciechowicz, Mary Shimoyama, Karen Yook, Jared Nedzel, Alex Jones, Brian Schilder, Avi Ma’ayan (Team Nitrogen, AGR and GTEx Data Stewards)
Contact point: Avi Ma'ayan firstname.lastname@example.org
Tags: KC1, Genotype-Tissue Expression, FAIRness, FAIR guidelines, model organisms
One of the main missions of the NIH Data Commons in the Pilot Phase was to improve the FAIRness of the selected three NIH-funded test cases resources: Genotype-Tissue Expression (GTEx), Alliance of Genome Resources (AGR), and Trans-Omics for Precision Medicine (TOPMed). To begin to achieve this goal key capability 1 (KC1) of the NIH Data Commons Pilot Phase (DCPPC) manually evaluated the digital assets readily available from these project’s web-sites. Specifically, manual FAIR assessments were performed on all GTEx and AGR web resources using FAIRshake. The results were analyzed and visualized within Jupyter notebooks, which communicate the strong FAIR compliant properties of these resources, as well as aspects of FAIRness that need improvement. An interactive webpage was created to summarize all the AGR FAIR assessment results. This webpage consolidates the results generated within the Jupyter notebooks to provide an overview across the various components within AGR. Results on the webpage are separated by resource type, datasets and tools, and by the members that compose the AGR consortium: the five model organism portals (MODs) and The Gene Ontology (GO) consortium. The results from the FAIR assessment analysis of the AGR and GTEx web resources were communicated to the AGR and GTEx Data Stewards representatives of the Data Commons. This prompted them to work on improving their scores by addressing some aspects of FAIRness that they overlooked, for example, adding a license, or API support with documentation.