Abstract
There exists a need of producing high-quality ontologies for Semantic Web applications that access legacy, relational and non-relational data sources. We present GF, a tool for materialization of ontologies from relational and non-relational data sources including H2 databases, CSV files and Excel spreadsheets. We evaluate a sample case generated by GF with a third-party ontology evaluation tool called OntoMetrics. We also introduce an scripting language for performing Ontology-Based Data Access allowing a semi-naive user to automate ontology generation and document ontologies by adding annotations. The results obtained show that the ontologies generated with GF are reasonably good for being used in Semantic Web applications because they are validated correctly and pass all of the filters for the OWL2 main profiles, thus making them suitable for processing with lightweight reasoners. The metrics originally indicated that our application was lacking quality in the annotation area regarding the documentation of the classes and properties generated by the application and that the functionality introduced by the scripting language allows to generate correctly annotated ontologies. An executable standalone application along with the data used in this paper are uploaded to a GitHub repository for reproducibility of the results presented here.
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Notes
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An online validator can be found at http://visualdataweb.de/validator/.
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OWL/RDF ontologies can be visualized with http://www.visualdataweb.de/webvowl/#.
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Acknowledgments
This research is funded by Secretaría General de Ciencia y Técnica, Universidad Nacional del Sur, Argentina and by Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC-PBA).
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Gómez, S.A., Fillottrani, P.R. (2022). Ontology Metrics and Evolution in the GF Framework for Ontology-Based Data Access. In: Pesado, P., Gil, G. (eds) Computer Science – CACIC 2021. CACIC 2021. Communications in Computer and Information Science, vol 1584. Springer, Cham. https://doi.org/10.1007/978-3-031-05903-2_16
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