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2017 | OriginalPaper | Buchkapitel

Collaborative Ontology Evolution and Data Quality - An Empirical Analysis

verfasst von: Nandana Mihindukulasooriya, María Poveda-Villalón, Raúl García-Castro, Asunción Gómez-Pérez

Erschienen in: OWL: Experiences and Directions – Reasoner Evaluation

Verlag: Springer International Publishing

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Abstract

Since more than a decade, theoretical research on ontology evolution has been published in literature and several frameworks for managing ontology changes have been proposed. However, there are less studies that analyze widely used ontologies that were developed in a collaborative manner to understand community-driven ontology evolution in practice. In this paper, we perform an empirical analysis on how four well-known ontologies (DBpedia, Schema.org, PROV-O, and FOAF) have evolved through their lifetime and an analysis of the data quality issues caused by some of the ontology changes. To that end, the paper discusses the composition of the communities that developed the aforementioned ontologies and the ontology development process followed. Further, the paper analyses the changes in those ontologies in the 53 versions of them examined in this study. Depending of the use case, the community involved, and other factors different approaches for the ontology development and evolution process are used (e.g., bottom-up approach with high automation or top-down approach with a lot of manual curation). This paper concludes that one model for managing changes does not fit all. Furthermore, it is also clear that none of the selected ontologies follow the theoretical frameworks found in literature. Nevertheless, in communities where industrial participants are dominant more rigorous editorial processes are followed, largely influenced by software development tools and processes. Based on the analysis, the most common quality problems caused by ontology changes include the use of abandoned classes and properties in data and introduction of duplicate classes and properties.

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Metadaten
Titel
Collaborative Ontology Evolution and Data Quality - An Empirical Analysis
verfasst von
Nandana Mihindukulasooriya
María Poveda-Villalón
Raúl García-Castro
Asunción Gómez-Pérez
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-54627-8_8

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