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Towards SHACL learning from knowledge graphs

Ghiasnezhad Omran, Pouya; Taylor, Kerry; Rodríguez Méndez, Sergio; Haller, Armin


Knowledge Graphs (KGs) are typically large data-first knowl- edge bases with weak inference rules and weakly-constraining data schemes. The SHACL Shapes Constraint Language is a W3C recommendation for the expression of shapes as constraints on graph data. SHACL shapes serve to validate a KG and can give informative insight into the structure of data. Here, we introduce Inverse Open Path (IOP) rules, a logical for- malism which acts as a building block for a restricted fragment of SHACL that can...[Show more]

CollectionsANU Research Publications
Date published: 2020
Type: Conference paper
Source: Proceedings of the 19th International Semantic Web Conference on Demos and Industry Tracks (ISWC)
Access Rights: Open Access


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