Trusting Decentralised Knowledge Graphs and Web Data at the Web Conference

Domingue, John; Third, Aisling; Vidal, Maria-Esther; Rohde, Philipp; Cano, Juan; Cimmino, Andrea and Verborgh, Ruben (2023). Trusting Decentralised Knowledge Graphs and Web Data at the Web Conference. In: Companion Proceedings of the ACM Web Conference 2023, ACM.



Knowledge Graphs have become a foundation for sharing data on the web and building intelligent services across many sectors and also within some of the most successful corporations in the world. The over centralisation of data on the web, however, has been raised as a concern by a number of prominent researchers in the field. For example, at the beginning of 2022 a €2.7B civil lawsuit was launched against Meta on the basis that it has abused its market dominance to impose unfair terms and conditions on UK users in order to exploit their personal data. Data centralisation can lead to a number of problems including: lock-in/siloing effects, lack of user control over their personal data, limited incentives and opportunities for interoperability and openness, and the resulting detrimental effects on privacy and innovation. A number of diverse approaches and technologies exist for decentralising data, such as federated querying and distributed ledgers. The main question is, though, what does decentralisation really mean for web data and Knowledge Graphs? What are the main issues and tradeoffs involved? These questions and others are addressed in this workshop.

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