Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 128 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 28 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 75 tok/s Pro
Kimi K2 189 tok/s Pro
GPT OSS 120B 432 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Using the Shapes Constraint Language for modelling regulatory requirements (2309.02723v1)

Published 6 Sep 2023 in cs.IT and math.IT

Abstract: Ontologies are traditionally expressed in the Web Ontology Language (OWL), that provides a syntax for expressing taxonomies with axioms regulating class membership. The semantics of OWL, based on Description Logic (DL), allows for the use of automated reasoning to check the consistency of ontologies, perform classification, and to answer DL queries. However, the open world assumption of OWL, along with limitations in its expressiveness, makes OWL less suitable for modelling rules and regulations, used in public administration. In such cases, it is desirable to have closed world semantics and a rule-based engine to check compliance with regulations. In this paper we describe and discuss data model management using the Shapes Constraint Language (SHACL), for concept modelling of concrete requirements in regulation documents within the public sector. We show how complex regulations, often containing a number of alternative requirements, can be expressed as constraints, and the utility of SHACL engines in verification of instance data against the SHACL model. We discuss benefits of modelling with SHACL, compared to OWL, and demonstrate the maintainability of the SHACL model by domain experts without prior knowledge of ontology management.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.