This event took place on 14 December 2021. Watch our events page for future workshops, webinars, and conferences.
The Semantic Web provides a graph-based organisation of knowledge that has become popular in enterprises under the term enterprise knowledge graphs.
It allows a lot of flexibility for modeling as well as combining data sets by linking graphs together, which has the potential to solve enterprise data heterogeneity problems in a bottom-up and flexible manner. When processing and linking together graph data in enterprises on a large scale, ETL (Extract-Transform-Load) processes supporting Semantic Web standards are used for automation. These processes, while being able to handle heterogeneity, have to consider a lot of different complex cases and therefore issues regarding inconsistencies and incompleteness in the data can occur.
To keep control of data quality, we use approaches to analyze and adapt the data so that inconsistencies can be taken into account for further actions or, if possible, the data is automatically repaired. The Semantic Web provides SHACL, the shapes constraint language, for graph data validation to detect inconsistencies regarding defined constraints and report them for further processing.
In this talk, we present an approach for validation and processing of inconsistencies to improve the quality for large knowledge graphs. We show a prototypical system which implements this in a high performance setup based on the RDFox triple store, where we combine SHACL validation with Datalog rules to demonstrate inconsistency management for practical use cases.
The team behind Oxford Semantic Technologies started working on RDFox in 2011 at the Computer Science Department of the University of Oxford with the conviction that flexible and high-performance reasoning was a possibility for data-intensive applications without jeopardising the correctness of the results. RDFox is the first market-ready knowledge graph designed from the ground up with reasoning in mind. Oxford Semantic Technologies is a spin-out of the University of Oxford and is backed by leading investors including Samsung Venture Investment Corporation (SVIC), Oxford Sciences Enterprises (OSE) and Oxford University Innovation (OUI).