Towards SHACL-based Knowledge Graph Transformation of Visual Domain Knowledge

Stefan Bischof, Erwin Filtz, Josiane Xavier Parreira, Simon Steyskal, Michael Baumgart, David Gruber, Maximilian Liebetreu, Florian Rötzer, Stephan Strommer

Published in: Posters and Demos Track of SEMANTiCS

2024

Abstract

Effective knowledge representation plays a pivotal role in harnessing the full potential of domain-specific information. Through tools like Infinity Maps, domain knowledge can be easily captured in a visual manner. However, translating these visually intuitive representations to formal, machine-processable formats often necessitates expert knowledge, thereby creating a significant barrier between domain experts and knowledge engineers. While domain experts possess deep understanding of their respective domains, they often lack the formalisation skills required to transform this knowledge into machine-readable formats. Conversely, knowledge engineers can design and implement sophisticated knowledge graphs, but may not have access to the domain-specific expertise necessary for effective knowledge representation. To address this challenge, we propose a novel approach that leverages SHACL (Shape Constraint Language) rules to transform visual domain knowledge expressed as Infinity Maps into knowledge graphs. Our method enables domain experts to define their knowledge structures using familiar Infinity Map representations, which are then transformed into standardised knowledge graphs compliant with the SHACL standard.