<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Semantic checking of railway infrastructure information support data is one of the ways to improve the consistency of information system data and, as a result, increase the safety of train traffic. Existing ontological developments have demonstrated the applicability of description logic for modelling railway transport, but have not paid enough attention to the data resources structure and the railway regulatory support. In this work, the formalization of the tabular presentation of data and the rules of railway transport regulations is carried out using the example of a connection track passport and temporary speed restrictions using ontological means, data wrangling and extraction tools. Ontologies of the various formats data resources and railway station infrastructure, tools for converting and extracting data have been developed. The semantic checking of the compliance of railway information system data with regulatory documents in terms of the connection track passport is carried out on the basis of a multi-level concretization model and integration of ontologies. The mechanisms for implementing the constituent ontologies and their integration are demonstrated by an example. Further research includes ontological checking of natural language normative documents of railway transport.</p>
</abstract>

Semantic checking of railway infrastructure information support data is one of the ways to improve the consistency of information system data and, as a result, increase the safety of train traffic. Existing ontological developments have demonstrated the applicability of description logic for modelling railway transport, but have not paid enough attention to the data resources structure and the railway regulatory support. In this work, the formalization of the tabular presentation of data and the rules of railway transport regulations is carried out using the example of a connection track passport and temporary speed restrictions using ontological means, data wrangling and extraction tools. Ontologies of the various formats data resources and railway station infrastructure, tools for converting and extracting data have been developed. The semantic checking of the compliance of railway information system data with regulatory documents in terms of the connection track passport is carried out on the basis of a multi-level concretization model and integration of ontologies. The mechanisms for implementing the constituent ontologies and their integration are demonstrated by an example. Further research includes ontological checking of natural language normative documents of railway transport.

Ontology-Based Semantic Checking of Data in Railway Infrastructure Information Systems

Ukrainian State University of Science and Technologies

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Semantic checking of railway infrastructure information support data is one of the ways to improve the consistency of information system data and, as a result,...

Ontology-Based Semantic Checking of Data in Railway Infrastructure Information Systems

Published Online: Oct 08, 2022

Page range: 291 - 319

Received: Dec 06, 2021

Accepted: Jul 12, 2022

DOI: https://doi.org/10.2478/fcds-2022-0016

Keywords
ontology, OWL, semantic checking, data validation, ontology integration, knowledge base, knowledge-based system, concept, information system

© 2022 Viktor Shynkarenko et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Ontology-Based Semantic Checking of Data in Railway Infrastructure Information Systems

Published Online: Oct 08, 2022

Page range: 291 - 319

Received: Dec 06, 2021

Accepted: Jul 12, 2022

DOI: https://doi.org/10.2478/fcds-2022-0016

Keywordsontology, OWL, semantic checking, data validation, ontology integration, knowledge base, knowledge-based system, concept, information system

© 2022 Viktor Shynkarenko et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
ontology, OWL, semantic checking, data validation, ontology integration, knowledge base, knowledge-based system, concept, information system