基本信息
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Bio
Paul Groth is Professor of Algorithmic Data Science at the University of Amsterdam where he leads the Intelligent Data Engineering Lab (INDElab). His research focuses on intelligent systems for dealing with large amounts of diverse contextualized knowledge with a particular focus on web and science applications. This includes research in data provenance, data integration and knowledge sharing.
Paul is scientific director of the UvA’s Data Science Center. Additionally, he is co-scientific director of two Innovation Center for Artificial Intelligence (ICAI) labs: The AI for Retail (AIR) Lab - a collaboration between UvA and Ahold Delhaize; and the Discovery Lab - a collaboration between Elsevier, the University of Amsterdam and VU University Amsterdam.
Previously, Paul led the design of a number of large scale data integration and knowledge graph construction efforts in the biomedical domain. Paul was co-chair of the W3C Provenance Working Group that created a standard for provenance interchange. He has also contributed to the emergence of community initiatives to build a better scholarly ecosystem including altmetrics and the FAIR data principles.
Paul is scientific director of the UvA’s Data Science Center. Additionally, he is co-scientific director of two Innovation Center for Artificial Intelligence (ICAI) labs: The AI for Retail (AIR) Lab - a collaboration between UvA and Ahold Delhaize; and the Discovery Lab - a collaboration between Elsevier, the University of Amsterdam and VU University Amsterdam.
Previously, Paul led the design of a number of large scale data integration and knowledge graph construction efforts in the biomedical domain. Paul was co-chair of the W3C Provenance Working Group that created a standard for provenance interchange. He has also contributed to the emergence of community initiatives to build a better scholarly ecosystem including altmetrics and the FAIR data principles.
Research Interests
Papers共 353 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2024)
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IEEE International Conference on Data Engineeringpp.301-304, (2024)
CoRR (2024)
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DEEM '24: Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learningpp.7-11, (2024)
PeerJ. Computer science (2024): e1781-e1781
DEEM@SIGMODpp.7-11, (2024)
CoRR (2024)
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arxiv(2024)
Semantic Webpp.1-25, (2024)
arxiv(2024)
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