Projects per year
Abstract
Knowledge Graphs (KGs) are widely used to represent heterogeneous domain knowledge on the Web and within organizations. Various methods exist to manage KGs and ensure the quality of their data. Among these, the Shapes Constraint Language (SHACL) and the Shapes Expression Language (ShEx) are the two state-of-the-art languages to define validating shapes for KGs. Since the usage of these constraint languages has recently increased, new needs arose. One such need is to enable the efficient generation of these shapes. Yet, since these languages are relatively new, we witness a lack of understanding of how they are effectively employed for existing KGs. Therefore, in this work, we answer How validating shapes are being generated and adopted? Our contribution is threefold. First, we conducted a community survey to analyze the needs of users (both from industry and academia) generating validating shapes. Then, we cross-referenced our results with an extensive survey of the existing tools and their features. Finally, we investigated how existing automatic shape extraction approaches work in practice on real, large KGs. Our analysis shows the need for developing semi-automatic methods that can help users generate shapes from large KGs.
Original language | English |
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Title of host publication | WWW 2022 - Companion Proceedings of the Web Conference 2022 |
Number of pages | 4 |
Publisher | Association for Computing Machinery |
Publication date | 25 Apr 2022 |
Pages | 260-263 |
ISBN (Electronic) | 9781450391306 |
DOIs | |
Publication status | Published - 25 Apr 2022 |
Event | 31st ACM Web Conference, WWW 2022 - Virtual, Online, France Duration: 25 Apr 2022 → … |
Conference
Conference | 31st ACM Web Conference, WWW 2022 |
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Country/Territory | France |
City | Virtual, Online |
Period | 25/04/2022 → … |
Sponsor | ACM SIGWEB |
Series | WWW 2022 - Companion Proceedings of the Web Conference 2022 |
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Bibliographical note
Publisher Copyright:© 2022 ACM.
Keywords
- Knowledge Graphs
- SHACL
- Shapes Extraction
- ShEx
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Poul Due Jensen Professorate in Big Data and Artificial Intelligence
Hose, K., Jendal, T. E. & Hansen, E. R.
01/11/2019 → 31/10/2024
Project: Research
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EDAO: EDAO: Example Driven Analytics for Open Knowledge Graphs
Lissandrini, M., Pedersen, T. B. & Hose, K.
15/09/2019 → 14/09/2021
Project: Research