FAIRy Stories: The FAIR Data Principles in Theory and in Practice

Carole Goble

University of Manchester

Wednesday, May 19, 2021. 9:00 a.m. (PT)

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The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program is proud to present Carole Goble in its 2021/2022 speaker series on Open Knowledge Networks. The series features researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data.

Abstract. The “FAIR Guiding Principles for scientific data management and stewardship” [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the armies of authors). Over the past 5 years, FAIR has become a movement, a mantra, and a methodology for scientific research and, increasingly, in the commercial and public sector. FAIR is now part of NIH, the European Commission, and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need.”

As a data infrastructure wrangler, I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-led approaches like Schema.org; work with big pharma on specialized FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.

In this talk, I will use some of these projects to shine some light on the FAIR movement. Spoiler alert: Although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role—not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”

[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18.

Bio: Carole Goble is a Professor of Computer Science at the University of Manchester, UK, where she leads a team of Researchers, Research Software Engineers, and Data Stewards. She has spent 25 years working in e-Science on reproducible science, open data and method sharing, knowledge and metadata management and computational workflows in a range of disciplines, and has led many scientific and e-Infrastructure projects and resources at the national and European level. She was an early pioneer of semantic web and linked data approaches in the Life Sciences.

Goble is extensively involved in ELIXIR, the pan-national European Research Infrastructures for Life Science data, and the European Open Science Cloud. She is a co-founder of the UK’s Software Sustainability Institute, coordinates the FAIRDOM infrastructure for research project assets management, and leads work at the international level on FAIR Research Objects and workflows. An advocate of FAIR and Open Data, she serves as the UK representative on the G7 Open Science Working Group and is one of the authors of the original FAIR data principles paper.

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NSF Convergence Accelerator Series Tracks A&B: Carole Goble