Prof. Dr. Michel Dumontier
Abstract | Semantic approaches for biomedical knowledge integration and discovery
With its focus on investigating the basis for the sustained existence of living systems, modern biology has always been a fertile, if not challenging, domain for knowledge management and discovery. Yet the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offers an exciting opportunity to reuse our collective knowledge, were it not stymied by incompatible formats, partial and overlapping standards, and heterogeneous data access.
In this talk, I will discuss our efforts to use a variety of knowledge representation and data mining technologies to wrangle biomedical knowledge into simple, but effective representations in order to generate and test hypotheses concerning drug repositioning and drug safety. As increased pressure mounts from researchers, publishers, and funders to provide FAIR (Findable, Accessible, Interoperable, and Reuseable) data, researchers worldwide need to be strategically poised to use these representations to pursue increasingly sophisticated discovery towards understanding human health and disease.
Dr. Michel Dumontier is a world-renowned researcher in the field of data science. After his work at the Stanford Center for Biomedical Informatics Research at Stanford University, he started as Distinguished Professor of Data Science at Maastricht University in January 2017.
His research focuses on the development of computational methods to increase the understanding of how living systems respond to chemical agents and how this response changes with genetic and environmental conditions.
Moreover, he advances the development of semantic web technologies to facilitate the investigation as well as the publishing and sharing of the vast amounts of biomedical data and knowledge.