Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges
- Autores
- Ferreirone, Mariano Julián; Lezoche, Mario; Franciosi, Chiara; Panetto, Hervé; Torres, Diego
- Año de publicación
- 2026
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Semantic web models such as ontologies and knowledge graphs were designed to represent knowledge explicitly and to infer implicit knowledge. This brings several benefits like flexibility and reasoning power. On the other hand, since the adoption of these models has been growing during the last years, the demand for consistency has risen in parallel. Therefore, the validation of these representations started to be an important issue for research. Several types of related works have been done; however, there is still a lack of an integrated review to understand the state of the art of formal semantic constraint validation. Addressing this issue is crucial for broader adoption of both the models discussed and the Semantic Web itself. For the community, it is important to review existing progress, outline future avenues, and examine related areas that can benefit from these developments. The contribution of this article includes a taxonomy of related research trends, a classification of selected works into these categories, and an overview of the main open challenges in validating semantic constraints for the Semantic Web. Each of these contributions was obtained through the conduction of a systematic literature review. In addition, an extension of the study is done to consider a very promising model which has a growing intersection with the field: property graphs. Finally, this paper concludes with an outlook that summarizes the contributions made and the challenges that the authors decided to continue researching in further steps.
- Materia
-
Ciencias de la Computación e Información
Knowledge Representation
Semantic Constraints
RDF Validation
Ontology
Knowledge Graph
Shapes Graphs - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
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- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/12686
Ver los metadatos del registro completo
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Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challengesFerreirone, Mariano JuliánLezoche, MarioFranciosi, ChiaraPanetto, HervéTorres, DiegoCiencias de la Computación e InformaciónKnowledge RepresentationSemantic ConstraintsRDF ValidationOntologyKnowledge GraphShapes GraphsSemantic web models such as ontologies and knowledge graphs were designed to represent knowledge explicitly and to infer implicit knowledge. This brings several benefits like flexibility and reasoning power. On the other hand, since the adoption of these models has been growing during the last years, the demand for consistency has risen in parallel. Therefore, the validation of these representations started to be an important issue for research. Several types of related works have been done; however, there is still a lack of an integrated review to understand the state of the art of formal semantic constraint validation. Addressing this issue is crucial for broader adoption of both the models discussed and the Semantic Web itself. For the community, it is important to review existing progress, outline future avenues, and examine related areas that can benefit from these developments. The contribution of this article includes a taxonomy of related research trends, a classification of selected works into these categories, and an overview of the main open challenges in validating semantic constraints for the Semantic Web. Each of these contributions was obtained through the conduction of a systematic literature review. In addition, an extension of the study is done to consider a very promising model which has a growing intersection with the field: property graphs. Finally, this paper concludes with an outlook that summarizes the contributions made and the challenges that the authors decided to continue researching in further steps.2026info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/12686enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.datak.2026.102604info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2026-04-16T09:44:58Zoai:digital.cic.gba.gob.ar:11746/12686Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412026-04-16 09:44:58.737CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
| dc.title.none.fl_str_mv |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| title |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| spellingShingle |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges Ferreirone, Mariano Julián Ciencias de la Computación e Información Knowledge Representation Semantic Constraints RDF Validation Ontology Knowledge Graph Shapes Graphs |
| title_short |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| title_full |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| title_fullStr |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| title_full_unstemmed |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| title_sort |
Semantic constraint validation in knowledge representation for the semantic web: A survey, taxonomy and research challenges |
| dc.creator.none.fl_str_mv |
Ferreirone, Mariano Julián Lezoche, Mario Franciosi, Chiara Panetto, Hervé Torres, Diego |
| author |
Ferreirone, Mariano Julián |
| author_facet |
Ferreirone, Mariano Julián Lezoche, Mario Franciosi, Chiara Panetto, Hervé Torres, Diego |
| author_role |
author |
| author2 |
Lezoche, Mario Franciosi, Chiara Panetto, Hervé Torres, Diego |
| author2_role |
author author author author |
| dc.subject.none.fl_str_mv |
Ciencias de la Computación e Información Knowledge Representation Semantic Constraints RDF Validation Ontology Knowledge Graph Shapes Graphs |
| topic |
Ciencias de la Computación e Información Knowledge Representation Semantic Constraints RDF Validation Ontology Knowledge Graph Shapes Graphs |
| dc.description.none.fl_txt_mv |
Semantic web models such as ontologies and knowledge graphs were designed to represent knowledge explicitly and to infer implicit knowledge. This brings several benefits like flexibility and reasoning power. On the other hand, since the adoption of these models has been growing during the last years, the demand for consistency has risen in parallel. Therefore, the validation of these representations started to be an important issue for research. Several types of related works have been done; however, there is still a lack of an integrated review to understand the state of the art of formal semantic constraint validation. Addressing this issue is crucial for broader adoption of both the models discussed and the Semantic Web itself. For the community, it is important to review existing progress, outline future avenues, and examine related areas that can benefit from these developments. The contribution of this article includes a taxonomy of related research trends, a classification of selected works into these categories, and an overview of the main open challenges in validating semantic constraints for the Semantic Web. Each of these contributions was obtained through the conduction of a systematic literature review. In addition, an extension of the study is done to consider a very promising model which has a growing intersection with the field: property graphs. Finally, this paper concludes with an outlook that summarizes the contributions made and the challenges that the authors decided to continue researching in further steps. |
| description |
Semantic web models such as ontologies and knowledge graphs were designed to represent knowledge explicitly and to infer implicit knowledge. This brings several benefits like flexibility and reasoning power. On the other hand, since the adoption of these models has been growing during the last years, the demand for consistency has risen in parallel. Therefore, the validation of these representations started to be an important issue for research. Several types of related works have been done; however, there is still a lack of an integrated review to understand the state of the art of formal semantic constraint validation. Addressing this issue is crucial for broader adoption of both the models discussed and the Semantic Web itself. For the community, it is important to review existing progress, outline future avenues, and examine related areas that can benefit from these developments. The contribution of this article includes a taxonomy of related research trends, a classification of selected works into these categories, and an overview of the main open challenges in validating semantic constraints for the Semantic Web. Each of these contributions was obtained through the conduction of a systematic literature review. In addition, an extension of the study is done to consider a very promising model which has a growing intersection with the field: property graphs. Finally, this paper concludes with an outlook that summarizes the contributions made and the challenges that the authors decided to continue researching in further steps. |
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2026 |
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2026 |
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eng |
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