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Mitchel Doktycz

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Advancing FAIR data towards comparable, organized, predictive AI-ready data for community validation

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By Elisha Wood-Charlson, Lindsey Anderson Verified, Mikayla A. Borton, Stephen K. Burley, Neil Byers, Ishwar Chandramouliswaran, Sylvain V Costes, Emiley A Eloe-Fadrosh, Christopher Henry, Oliver Fiehn, Mahantesh Halappanavar, Marcin P. Joachimiak, Sean P. Jungbluth, Julia Koblitz, Gazi Mahmud, Lee Ann McCue, Thomas Metz, Nigel J. Mouncey, Christopher Mungall, Tiffanie M Nelson, Amanda M. Saravia-Butler, Susannah G. Tringe, Tim Van Den Bossche, Adam Arkin, Wolmar N. Åkerström, Paramvir S. Dehal, Mitchel Doktycz, Kjiersten Fagnan, Bonnie Hurwitz, Valerie Skye, V. Ratna Saripalli
| Nature Verified
Abstract The interrogation of data across biological and environmental systems has become increasingly complex. Fortunately, communities are adopting the FAIR (Findable, Accessible, Interoperable, Reusable) data principles for individual datasets, and continue to develop domain-specific, machine-actionable standards. However, integrating FAIR data for meta-analysis across data resources is still challenging.
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