This year’s Stifterverband Science Award “Society Needs Science” goes to L3S member Prof. Dr. Maria-Esther Vidal, Head of the “Scientific Data Management” research group at TIB – Leibniz Information Centre for Science and Technology in Hannover. The award honours the computer scientist’s work on scientific data management. The award, worth €50,000 in total, was conferred at the Leibniz Association’s Annual Meeting, which was held virtually this year.
Managing large volumes of research data is one of the key challenges facing science. Data from different sources need to be prepared, consolidated and harnessed so that their combination can generate new insights. Maria-Esther Vidal focuses on this issue by conducting research on optimising database queries, the visualisation of data through knowledge graphs on the Semantic Web, an enrichment of web data with structured data, and big data analysis.
Her work focuses in particular on semantic data management in biomedicine and life sciences. The consolidation of extensive and heterogeneous datasets promises to pave the way for numerous new approaches to treat diseases. For example, Maria-Esther Vidal is working on transforming clinical and genomic data (OMICS) into semantic knowledge graphs, which describe individual signatures of patients, facilitating personalised treatment methods based on integrated profiles of the patients. One concrete application example in medicine is research into drug interactions and various other factors affecting life expectancy with lung cancer.
The combination of information from very different sources, ranging from scientific publications, statistical analyses, and genetic information to chemical structural formulae, allows systematic analyses and predictions to be made where, in the past, they were usually only possible on an ad hoc and unsystematic basis. For this purpose, Maria-Esther Vidal and the members of the Semantic Data Management group (SDM) have developed a platform that combines more than 40 different data sources and uses knowledge graphs and machine learning to enable scientists to discover, understand and predict patterns.
In collaboration with a Greek research group, the group led by Maria-Esther Vidal is currently using this method to develop a knowledge graph on drug interactions based on scientific literature and databases, which may be worth considering in the treatment of COVID-19. (See, for example, https://blogs.tib.eu/wp/tib/2020/05/06/how-do-knowledge-graphs-contribute-to-understanding-covid-19-related-treatments/ and https://devpost.com/software/covid-19-kg).
The computer science techniques used by Maria-Esther Vidal to structure knowledge and integrate data are not limited to applications in medicine; they can, in principle, be used in a wide range of multidisciplinary contexts beyond science, such as in industry. All software tools developed by Maria-Esther Vidal’s research group are freely available worldwide for research and application in the form of open-source software.
The Photograph shows Maria-Esther Vidal, Volker Meyer-Guckel (Deputy Secretary General of the Stifterverband) and President of the Leibniz Association Matthias Kleiner (from left) at the award ceremony // Photo: TIB/C. Bierwagen