Science goes FAIR at Health-RI 2017

What does FAIR Data mean in practice? How can you make your data FAIR? What novel science becomes possible when research data become more FAIR? Luiz Bonino and Michel Dumontier will answer these pressing questions at the Health-RI conference on 8 December 2017 in Utrecht.

FAIR Data is rapidly becoming the new standard in science. A FAIR data backbone is also the core of Health-RI. In the past few years, DTL has coordinated the development of an eco-system of software solutions to support research data FAIRification. Dr Luiz Bonino has lead these developments as the Chief Technology Officer for FAIR Data at DTL. In the 8 December presentation, he will demonstrate the elements of the FAIR eco-system in practice, from non-FAIR data to data that are integrated with other FAIR data in an end-user application.

Luiz Bonino

Accelerating scientific discovery with FAIR

Dr Michel Dumontier is a Distinguished Professor of Data Science at Maastricht University. His research focuses on the development of computational methods for scalable integration and reproducible analysis of FAIR data across scales – from molecules, tissues, organs, individuals, and populations, to the environment. Dumontier: “With its focus on investigating the basis for the sustained existence of living systems, modern biology as always been a fertile, if not challenging, domain to represent knowledge amenable to computational-based discovery. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offers an exciting opportunity to reuse our collective knowledge, were we not stymied by incompatible formats, partial and overlapping standards, and heterogeneous data access.”

“In my talk on 8 December, I will discuss our efforts to develop computational frameworks and methods to wrangle knowledge into simple, but effective representations and to make these FAIR. Our work sets the stage for a global revolution to take advantage of the data we already have and to increase our confidence and the evidence in reporting, validating, and generating novel scientific discoveries.”

Michel Dumontier

Profile Luiz Bonino

Luiz Bonino is the Chief Technology Officer for FAIR Data at the Dutch Techcentre for Life Sciences and Associate Professor at the Human Genetics department of the Leiden University Medical Centre. He holds a Ph.D. in Computer Sciences from the University of Twente in the areas of conceptual modeling, ontology engineering, semantic interoperability, service-oriented computing, context-aware computing and requirements engineering. With a mixed background on both academic and industrial environments, he leads an international team working on technical solutions for FAIR Data. He is also involved in the FAIR metrics working group and in the architectural efforts of the Personal Health Train, among others.

Profile Michel Dumontier

Dr Michel Dumontier’s group combines semantic web technologies with effective indexing, machine learning and network analysis for drug discovery and personalized medicine. Previously at Stanford University, Dr. Dumontier now leads a new inter-faculty Institute for Data Science at Maastricht University with a focus on accelerating scientific discovery, improving health and well-being, and strengthening communities. He is a Principal Investigator for the NCATS Biomedical Data Translator and a co-Investigator for the NIH BD2K Center for Expanded Data Annotation and Retrieval (CEDAR). He is a technical lead for the FAIR (Findable, Accessible, Interoperable, Re-usable) data initiative, and is the scientific director for Bio2RDF, an open source project to generate Linked Data for the Life Sciences. He is the editor-in-chief for the IOS press journal Data Science and an associate editor for the IOS press journal Semantic Web. He is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies as evidenced by awards, keynote talks at international conferences, and collaborations on international projects.

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