An ontology-based data access framework for enhanced sewer network management

Effective urban water network management is often hindered by data heterogeneity and a severe lack of interoperability. This study leverages the power of the Semantic Web to introduce a new application ontology, the SewerNetworkOntology, coupled to an Ontology-Based Data Access (OBDA) framework specifically designed for sewer network management. Our framework integrates a specifically designed conceptual layer, representing the physical structures of these networks, linked to a data layer through formalised mappings. A key contribution is the framework’s ability to automatically identify data inconsistencies that remain hidden with traditional methods. We demonstrate the effectiveness of our system through its application to the wastewater and stormwater networks of Montpellier Métropole.

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Publication Details

Journal
Digital Water
Published
2026-08-27
DOI
https://doi.org/10.1080/28375807.2026.2725896
Primary Topic
Urban Stormwater Management Solutions
Type
article
Field-Weighted Citation Impact
0.00

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article

An ontology-based data access framework for enhanced sewer network management

Nanée Chahinian, Umberto Straccia, Claude Pasquier, Batoul Haydar
Digital Water
Urban Stormwater Management Solutions
article

An ontology-based data access framework for enhanced sewer network management

Nanée Chahinian, Umberto Straccia, Claude Pasquier, Batoul Haydar
article en

Abstract

Effective urban water network management is often hindered by data heterogeneity and a severe lack of interoperability. This study leverages the power of the Semantic Web to introduce a new application ontology, the SewerNetworkOntology, coupled to an Ontology-Based Data Access (OBDA) framework specifically designed for sewer network management. Our framework integrates a specifically designed conceptual layer, representing the physical structures of these networks, linked to a data layer through formalised mappings. A key contribution is the framework’s ability to automatically identify data inconsistencies that remain hidden with traditional methods. We demonstrate the effectiveness of our system through its application to the wastewater and stormwater networks of Montpellier Métropole.

Digital Water
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT), Centre National de la Recherche Scientifique (FR), Université de Montpellier (FR), Observatoire de la Côte d’Azur (FR), Institut de Recherche pour le Développement (FR)
European Commission, Agence Nationale de la Recherche, H2020 Marie Skłodowska-Curie Actions
Clean water and sanitation
Openalex Percentile: Top 17%
Urban Stormwater Management Solutions
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