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OOPS!: A Pitfall-Based System for Ontology Diagnosis
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Author(s): María Poveda-Villalón (Universidad Politécnica de Madrid, Spain), Asunción Gómez-Pérez (Universidad Politécnica de Madrid, Spain)and Mari Carmen Suárez-Figueroa (Universidad Politécnica de Madrid, Spain)
Copyright: 2018
Pages: 29
Source title:
Innovations, Developments, and Applications of Semantic Web and Information Systems
Source Author(s)/Editor(s): Miltiadis D. Lytras (American College of Greece, Greece), Naif Aljohani (King Abdulaziz University, Saudi Arabia), Ernesto Damiani (University of Milan, Italy)and Kwok Tai Chui (The Open University of Hong Kong, Hong Kong)
DOI: 10.4018/978-1-5225-5042-6.ch005
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Abstract
The first contribution of this paper consists on a live catalogue of pitfalls that extends previous works on modeling errors with pitfalls resulting from an empirical analysis of numerous ontologies. Such a catalogue classifies pitfalls according to the Structural, Functional and Usability-Profiling dimensions. For each pitfall, we include the value of its importance level (critical, important and minor). The second contribution is the description of OntOlogy Pitfall Scanner (OOPS!), a widely used tool for detecting pitfalls in ontologies and targeted at newcomers and domain experts unfamiliar with description logics and ontology implementation languages. The tool operates independently of any ontology development platform and is available through a web application and a web service. The evaluation of the system is provided both through a survey of users' satisfaction and worldwide usage statistics. In addition, the system is also compared with existing ontology evaluation tools in terms of coverage of pitfalls detected.
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