Query-driven analytics in graph databases
Graphs are becoming pervasive in several unconventional applications where connectivity needs to be leveraged for querying and analytical purposes. Such applications areas include the Semantic Web, Social Networks, Fraud Detection applications, Recommendation Systems and Knowledge Bases. At the heart of these applications lays the property graph data model as the common ground defining the foundations of current graph database systems. In this talk, I will provide a systematic view on query-driven analytics in graph databases. I will elucidate the needed requirements and open challenges for this emerging field.
Angela Bonifati is a Full Professor of Computer Science at Lyon 1 University (France), where she leads the Database Group. She received her PhD from Politecnico di Milano in 2002 and was a postdoctoral researcher at INRIA Paris until 2003. Her current research interests are on the interplay of relational and graph-oriented data paradigms, particularly on query processing, data integration and data curation, metadata management and learning. On these topics, she has co-authored more than 100 publications in top-tier database conferences and journals. She is the Program Chair of EDBT 2020, an Associate Editor of PVLDB (2020-2022), the Demo Co-Chair of ICDE 2020 and the Sigmod 2019 and Sigmod 2020 Workshops Co-chair. She was Vice Chair of ICDE 2018 and ICDE 2011. She is an Associate Editor for several journals, including the VLDB Journal, ACM TODS and Distributed and Parallel Databases. She holds several visiting positions, the latest of which at the University of Waterloo (Canada) in 2019.
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