Implementing FAIR data for people and machines: Impacts and implications - results of a research data community workshop

Authors:
Open Access
Publisher website
Google Scholar
Abstract
The Implementing FAIR Data for People and Machines: Impacts and Implications workshop was organized by the Board on Research Data and Information of the National Academies of Sciences, Engineering, and Medicine (NASEM), the CENDI Federal Information Managers Group, the Research Data Alliance (RDA), and the National Federation of Advanced Information Services (NFAIS), and held at NASEM’s Keck Center in Washington, DC on September 11, 2019. The goals of the Implementing FAIR Data workshop were to discuss the current status of FAIR data implementation, share what is being done to encourage scientists to share data in machine-readable formats, and examine the implications of FAIR data implementation for people and machines. FAIR data policies, tools, and measures of FAIR data compliance were considered from multiple perspectives. Marcia McNutt, President of the National Academy of Sciences (NAS), offered opening remarks, and the keynote address was presented by Barend Mons, Professor of Bioinformatics at Leiden University Medical Center and President of the International Science Council’s Committee on Data (CODATA). Three panel discussions addressed (1) the perspectives of scientists and administrators from U.S. federal agencies, (2) case studies on the implementation of FAIR data practices, and (3) principles and methods of measuring FAIR data compliance. The automation of scientific workflows was discussed by Stuart Feldman, Chief Scientist of Schmidt Futures, a philanthropic organization devoted to investing in research, technology, and science. The workshop closed with highlights and takeaways from each session as summarized by the moderators, followed by general questions.

This publication has 18 references indexed in Scilit: