Kristina Hettne (1978), PhD, is a Digital Scholarship Librarian at the Centre for Digital Scholarship, Leiden University Libraries in Leiden, The Netherlands. She obtained her master in computer science from Skövde University in Sweden in 2003 and shortly thereafter joined the computational toxicology group at AstraZeneca R&D in Mölndal, Sweden as a research scientist. In 2006, she moved to the Netherlands to pursue her PhD degree in bioinformatics of toxicogenomics, which she obtained from the University of Maastricht in 2012. In 2011 she joined the BioSemantics group at the Leiden University Medical Center as postdoctoral researcher. From 2015 to 2018 she led the group’s research on knowledge discovery applications as a senior researcher. In October 2018 she joined the Centre for Digital Scholarship at the Leiden University Libraries as a Digital Scholarship Librarian, where she helps researchers navigate Open Science and shape the future of research data management. She is the Centre’s liaison with GO FAIR and part of the FAIR Convergence Matrix development team for optimizing the reuse of existing FAIR-related resources. She is a review editor for “Frontiers in Big Data”, member of the Advisory Board of the Wiley journal “Genetics & Genomics Next”, and co-author of more than 30 research publications.
Orcid: https://orcid.org/0000-0002-4182-7560
Impactstory: https://profiles.impactstory.org/u/0000-0002-4182-7560/
Twitter: @KristinaHettne

Presentation:
Narrowing the gap between international FAIR Best Practices for Open Science and University implementation
Leiden University (LU) adapted a data management regulation in 2016. The regulation embraces the Findable, Accessible, Interoperable and Reusable (FAIR) principles. To implement the regulation a programme was established. The focus of the programme was in first instance to raise awareness and setup services to make data and software Findable and Accessible and to train researchers on data management planning. In 2019 the programme has entered its second phase with an increased focus on implementing the machine-actionable aspects of FAIR. In addition, a programme dedicated to Open Science is due to start in 2020. The presentation will look at how LU closes the feedback loop between emerging Best Practices for implementation of the FAIR principles for Open Science from international organisations while keeping the focus on the researcher. LU engages closely with the international bottom-up organisations GO FAIR, the Research Data Alliance (RDA) and CODATA. In this way LU can accelerate the uptake and availability of the emerging best practices and judge better the suitability of solutions to its researchers. The presentation will touch upon setting up Bring Your Own Data FAIRification and Open Science workshops, the development of a terminology for FAIR stewardship skills, and introduce the FAIR Convergence Matrix for optimizing the reuse of existing FAIR-related resources.