Head of the Scientific Data Management Group and Professor, German National Library of Science and Technology (TIB)
Prof. Dr. (Univ. Simón Bolívar) Maria-Esther Vidal leads the Scientific Data Management (SDM) group at TIB and the Leibniz joint-lab with the L3S Research Centre, and she is a full professor (on-leave) at Universidad Simón Bolívar (USB), Venezuela. She has made significant contributions to data management, semantic data integration, and machine learning over knowledge graphs. She is a co-author of over 150 peer-reviewed articles in Semantic Web, Databases, Bioinformatics, and Artificial Intelligence. She is also actively shaping her research communities, e.g., as an editorial board member of renowned journals (e.g., JWS, JDIQ), as well as general chair, co-chair, senior reviewer of major scientific events (e.g., WWW, ISWC, AAAI, AMW, KDE). She has been very successful in acquiring third-party funds, and since 2016, she participates in a leading role in five EU H2020 projects and two MSCA-ETN, among others. Specifically, she is actively contributing to a paradigm shift in biomedicine and leading the development of knowledge graphs to support precision medicine in the projects iASiS, BigMedilytics, CLARIFY, P4-LUCAT, and ImProVIT. Under her direction, her team has developed technologies of predominant relevance in the whole process of knowledge graph creation from heterogeneous data and research data management. She serves as an expert in advisory boards and several summer schools and doctoral consortiums. She has advised more than 20 doctoral students and more than 120 Master and bachelor students in Computer Science. She has been a doctoral and habilitation committee member in France, Italy, the Netherlands, Germany, Ireland, the US, Argentina, Uruguay, and Venezuela. From 2016 to 2018, she was a senior research scientist at the Fraunhofer Institute (IAIS). She has also been a visiting professor with long-term stays at the University of Maryland (UMD), the University of Nantes, the Karlsruhe Institute of Technology, University of Bonn, the Polytechnic University of Madrid, and the Polytechnic University of Barcelona. For more than 15 years, she has participated in ten projects funded by the US National Science Foundation (NSF) - in collaboration with UMD.
Maria-Esther is speaking at
This track will bring together leading initiatives that are paving the way for what could become functional implementations of European-governed data sharing spaces. For Europe to compete at an international level, its smaller but highly diversified data producers need to join forces. The European Data Strategy outlines a roadmap to enable and realise data sharing spaces as a means to power up AI in Europe by increasing access to data. The longterm vision is for an initial number of sector-based data sharing spaces to interoperate. The need to comply with European values, ethics and legislation when handling data should not be considered restrictive, but as a safeguard for risk-free data sharing that encourage increased participation. In this track, we want to move beyond the ‘What’ and consider ‘How’ all this can be achieved through convergence and standardization efforts by projects, organisations and other entities possessing the right technical know-how, experiences and commitment.
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