“FAIR – Findable Accessable Interoperable Reusable”. The “FAIR Principles” for research data, software, computational workflows, scripts, or any kind of Research Object has become a mantra. It’s embedded in EU and UK research roadmaps. It’s become funder and publisher policy. How can one argue with the idea of data and software being “FAIR”? Surely FAIR data is a prerequisite for data to be AI ready and the very foundation of Data Science?
For the past 15 years I have been working on building a FAIR research commons in the Life Sciences in a range of projects and initiatives. Some initiatives are top-down like the European Research Infrastructures. Some are bottom-up, supporting FAIR for investigator-led projects, biodiversity analytics, and FAIR drug discovery. Some have become movements, like Bioschemas, the Common Workflow Language and Research Objects. Others focus on cross-cutting approaches in reproducibility, computational workflows, metadata representation and scholarly sharing & publication.
As co-author of the FAIR Principles for data (and recent extensions to software and workflows) I have some ideas about why FAIR hit home, as well as the challenges in bringing principles to practice (some expected and some surprising). In this talk I will relate a series of FAIRy tales and the implications of FAIR for Data Science.
 Mark Wilkinson, Michel Dumontier et al The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data volume 3, article number: 160018 (2016), https://www.nature.com/articles/sdata201618
Carole Goble has spent her career wrangling semantics, software and scientists. Carole Goble is a Full Professor in the School of Computer Science where she leads a team of researchers and software developers working in e-Science, building e-infrastructure for researchers working at the lab, national, and pan-national level. She applies technical advances in knowledge technologies, distributed computing, workflows and social computing to solve information management problems for Life Scientists, especially Systems Biology, and other scientific disciplines, including Biodiversity, Chemistry, Health informatics and Astronomy. Her current research interests are in open and reproducible research, digital object curation and preservation, semantic interoperability, knowledge exchange between scientists and FAIR computational workflows.
She has leadership roles in European data infrastructure for the life sciences (Head of ELIXIR-UK, ELIXIR Interoperability Platform, IBISBA data platform, FAIRDOM initiative) and is co-founder of the UK’s Software Sustainability Institute. She is a partner on the IMI FAIRplus project working with Pharmaceutical companies on “FAIRifying their data” and many other projects. She is one of the authors of the influential FAIR Data Principles Nature paper and has been active in national and European policy making. In 2008 she was awarded the Microsoft Jim Gray award for outstanding contributions to e-Science.