SHACL-based Ontology Design Patterns for Evidence-based Decision-making

This work proposes an application of Semantic Web SHACL-defined constraints to detect premature information in decision-making. We frame these as ontology design patterns to facilitate domain experts in building Semantic Web-based ontologies for detecting premature information. This helps decision-makers to move from intuition-based decision-making to evidence-based decision-making.
This work also explores the use of ontology design patterns for business rules, for reasoning beyond inferencing, and for end-user interfaces. While this work’s context lies in the Semantic Web’s traditional focus on data integration and inferencing, we focus here on how SHACL’s constraint logic builds on top of this. The result approaches implementing business rule system logic that can apply to the integrated big data of the Semantic Web.
We detect the completeness, reproducibility, consensus, and conflict violations using Semantic Web constraints. Domain experts can re-use the evidence-based management pattern and apply it for their decisions. We use requirement prioritization as an example of a decision from software product management to validate our approach.