Did You Validate Your Ontology? OOPS!

Abstract

Abstract. The application of methodologies for building ontologies can improve ontology quality. However, such quality is not guaranteed because of the difficulties involved in ontology modelling. These difficulties are related to the inclusion of anomalies or bad practices within the ontology development. Several authors have provided lists of typical anomalies detected in ontologies during the last decade. In this context, our aim in this paper is to describe OOPS! (OntOlogy Pitfall Scanner!), a tool for detecting pitfalls in ontologies.Keywords: pitfalls, bad practices, ontology evaluation, ontology engineering IntroductionThe growing interest during the last decades of practitioners in ontology development methodologies have supposed a step forward in transforming the art of building ontologies into an engineering activity. The correct application of such methodologies benefits ontology quality. However, such quality is not totally guaranteed because developers must tackle a wide range of difficulties and handicaps when modelling ontologies [1,2,5,8]. These difficulties can imply the appearance of the so-called anomalies or bad practices in ontologies. Therefore, it is important to evaluate the ontologies before using or reusing them in other ontologies or semantic applications. One of the crucial issues in ontology evaluation is the identification of anomalies in the ontologies. In this regard, it is worth mentioning that Rector et al. [8] describe a set of common errors made by developers during the ontology modelling. Moreover, Gómez-Pérez [4] proposes a classification of errors identified during the evaluation of different features such as consistency, completeness, and conciseness in ontology taxonomies. Finally, Poveda et al. [7] identify an initial catalogue of common pitfalls.In this context, our goal within this paper is to present an automated tool to help ontology practitioners by detecting common pitfalls during the ontology development. This tool is called OOPS! (OntOlogy Pitfall Scanner!) and represents a new option for ontology developers within ontology evaluation tools as it enlarges the list of errors detected by most recent and available works (e.g. MoKi 1 [6] and XD Analyzer 2 ). In addition, OOPS! can be executed independently of the ontology development plat-1 https://moki.fbk.eu/moki/tryitout/index.php/Main_Page (Last visit on 14-04-2012) 2 http://neon-toolkit.org/wiki/XDTools (Last visit on: 14-04-2012)

Distributional semantics for ontology verification

“…But the objective of the present work is different, pertaining to ontology debugging, which covers a wide range of techniques, from syntactic verifications (Poveda-Villalón et al, 2012) to anti-patterns detection (Roussey and Zamazal, 2013), both based on common modeling mistakes, or the submission of models (Ferré and Rudolph, 2012;Benevides et al, 2010) or consequences (Pammer, 2010) of the input ontology to the user. As discussed in section 6, the framework depicted here presents an interesting complementarity with debugging techniques developed in the Description Logics community, prototypically based on diagnosis (Friedrich and Shchekotykhin, 2005;Kalyanpur et al, 2006;Qi et al, 2008;Ribeiro and Wassermann, 2009), because they require the prior identification of some undesired consequence of K (be it ⊥).…”