Wikidata ( Communications of the ACM 57 (2014) 78–85), the open knowledge graph maintained by the Wikimedia Foundation, continues to expand its role as a central hub of structured data for Wikipedia and its sister projects, as well as an increasingly vital resource for academic research and industrial applications. Its collaborative nature, blending human and machine contributions, creates unique opportunities and challenges at the intersection of knowledge representation, data management, and socio-technical systems. The growing academic interest in Wikidata has been exemplified by initiatives like the annual Wikidata Workshop at the International Semantic Web Conference (ISWC) (Proceedings of the 4th Wikidata Workshop (2024) CEUR Workshop Proceedings; Proceedings of the 3rd Wikidata Workshop (2023) CEUR Workshop Proceedings). These efforts have fostered a vibrant research community investigating both the technical aspects of Wikidata and its socio-technical ecosystem. Building on this momentum, this special issue of the Semantic Web Journal brings together cutting-edge research to explore the opportunities and challenges posed by this collaborative knowledge graph.
Building similarity graph...
Analyzing shared references across papers
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Kaffee et al. (Sun,) studied this question.
synapsesocial.com/papers/68c1e17054b1d3bfb60fe8e4 — DOI: https://doi.org/10.3233/sw-243786
Lucie-Aimée Kaffee
University of Copenhagen
Simon Razniewski
Center for Scalable Data Analytics and Artificial Intelligence
Pavlos Vougiouklis
Huawei Technologies (United Kingdom)
Semantic Web
Technische Universität Dresden
Huawei Technologies (United Kingdom)
Building similarity graph...
Analyzing shared references across papers
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