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Barend Mons
 
Prof. Dr. Barend Mons holds a chair in Biosemantics at the Leiden University Medical Centre and is Head of Node for The Netherlands in ELIXIR . In addition he acts as a Life Sciences 'eScience integrator' in the Netherlands e-Science centre. Barend is also a member of the Executive Committee of the IMI project Open PHACTS, and one of the Founders of the Concept Web Alliance. He also serves on several Scientific and Technical Advisory Boards. Currently, he also advises a startup company that was built around nanopublications, called EURETOS.
 
Barend is a molecular biologist by training and received his MsC in Biology (cum laude) in 1981 and his PhD in 1986 on genetics of malaria parasites, from Leiden University, The Netherlands. Subsequently he performed over a decade of research on malaria genetics and vaccine development in close collaboration with colleagues in developing countries. He served the research department of the European Commission in this field for 3 years as a seconded national expert and did gain further experience in science management at the Research council of The Netherlands (NWO). Barend was a co-founder of three spin-off companies in biotechnological and semantic technologies, and an advisor for several others.
 
In the year 2000, Barend switched to the development of semantic technologies to manage big data and he founded the Biosemantics group. At present, Barend is Professor in Biosemantics at the at the Department of Human Genetics at the Leiden University Medical Centre with an honorary appointment in the same discipline at the Department of Medical Informatics, Erasmus Medical Centre, University of Rotterdam, both in The Netherlands. From 2009-2014 he was also Scientific Director of the Netherlands Bioinformatics Center (NBIC) and board member of the interim ELIXIR international board. His research is focused on nanopublications as a substrate for in silico knowledge discovery.
 
Abstract: "Data stewardship, boring or soaring?"
 
In the eScience era, meaningful pattern recognition in high dimensional and complex data has a major contribution to knowledge discovery in science, specifically chemistry and biology, whether it be in drug discovery or materials development. In order to optimally (re-)use data for this purpose, the data need to be machine-readable. However, many key data sets and databases are not in enabling formats and most research projects do not even have a “data management plan” that deals with the generated data for the duration of the project. Many key data sets therefore go unnoticed or worse, get lost. Data stewardship emphasizes the long-term availability of data for continued use in human and machine meta-analyses. This talk will cover aspects of data publishing in FAIR format (Findable, Accessible, Interoperable and Reusable). It will also show how well stewarded data can serve “in silico knowledge discovery” and may change the metrics of scientific attribution. Specifically interaction between traditionally separated chemical and biological data will be addressed.