Angela Bonifati

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About

Angela Bonifati is a leading researcher in data management, with a focus on graph databases, query processing, and semantic web technologies. Her work bridges theoretical foundations and practical systems, particularly in the analysis of large-scale knowledge graphs. She is best known for her pioneering analysis of Wikidata query logs, as exemplified by her highly cited 2019 paper “Navigating the Maze of Wikidata Query Logs” (65 citations), which uncovered unexpected patterns in how users interact with this massive collaborative knowledge base. This research has significantly advanced our understanding of real-world query workloads, influencing the design of more efficient graph query engines and benchmarking tools. Bonifati’s contributions extend to query optimization, data integration, and provenance management, with her work appearing in top venues like SIGMOD, VLDB, and ICDE. She has also co-authored influential surveys on graph query languages and has been recognized with best paper awards. Her research continues to shape how complex, interconnected data is queried and analyzed, making her a key figure in modern data systems.