ODEval: A Tool for Evaluating RDF(S), DAML+OIL, and OWL Concept Taxonomies

Corcho, Óscar; Gómez-Pérez, Asuncíon; González-Cabero, Rafael; Suárez-Figueroa, M. Carmen

doi:10.1007/1-4020-8151-0_32

Cited by 26 publications

(14 citation statements)

References 4 publications

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“…In the recent years, several linguistic and knowledge resources have been built, either manually or automatically. WordNet 3 , Cyc 4 and SUMO 5 are examples of manually built resources. WordNet is by far the most widespread.…”

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confidence: 99%

Imposing a Semantic Schema for the Detection of Potential Mistakes in Knowledge Resources

Maltese

2013

Lecture Notes in Computer Science

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confidence: 99%

Imposing a Semantic Schema for the Detection of Potential Mistakes in Knowledge Resources

Maltese

2013

Lecture Notes in Computer Science

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“…In 2002 Fernández-López and Gómez-Pérez [7] developed ODEClean providing technological support to OntoClean Method [19] in the form of a plug-in for the WebODE ontology development environment. Few years later, ODEval 4 [4] was developed to help users evaluating RDF(S) and DAML+OIL concept taxonomies. Within those tools that support OWL ontologies we can find some developed as plug-ins for desktop applications as XDTools plug-in for NeOn Toolkit and OntoCheck plug-in for Protégé.…”

Section: State Of the Artmentioning

confidence: 99%

Validating Ontologies with OOPS!

Poveda‐Villalón

Suárez-Figueroa

Gómez-Pérez

2012

Lecture Notes in Computer Science

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119

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Abstract. Ontology quality can be affected by the difficulties involved in ontology modelling which may imply the appearance of anomalies in ontologies. This situation leads to the need of validating ontologies, that is, assessing their quality and correctness. Ontology validation is a key activity in different ontology engineering scenarios such as development and selection. This paper contributes to the ontology validation activity by proposing a web-based tool, called OOPS!, independent of any ontology development environment, for detecting anomalies in ontologies. This tool will help developers to improve ontology quality by automatically detecting potential errors. Keywords: ontology, pitfalls, ontology evaluation, ontology validation IntroductionThe emergence of ontology development methodologies during the last decades has facilitated major progress, transforming the art of building ontologies into an engineering activity. The correct application of such methodologies benefits the ontology quality. However, such quality is not always guaranteed because developers must tackle a wide range of difficulties and handicaps when modelling ontologies [1,2,11,15]. These difficulties can imply the appearance of anomalies in ontologies. Therefore, ontology evaluation, which checks the technical quality of an ontology against a frame of reference [18], plays a key role in ontology engineering projects. Ontology evaluation, which can be divided into validation and verification [18], is a complex ontology engineering process mainly due to two reasons. The first one is its applicability in different ontology engineering scenarios, such as development and reuse, and the second one is the abundant number of approaches and metrics [16].One approach for validating ontologies is to analyze whether the ontology is conform to ontology modelling best practices; in other words, to check whether the ontologies contain anomalies or pitfalls. In this regard, a set of common errors made by developers during the ontology modelling is described in [15]. Moreover, in [10] a classification of errors identified during the evaluation of different features such as consistency, completeness, and conciseness in ontology taxonomies is provided. Finally,in [13] authors identify an initial catalogue of common pitfalls.In addition, several tools have been developed to alleviate the dull task of evaluating ontologies. These tools support different approaches like (a) to check the consistency of the ontology, (b) to check the compliance with the ontology language used to

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“…Finally, [8] introduces the ODEval tool that can be used that can be used to detect possible taxonomical problems in ontologies, such as inconsistency, incompleteness, and redundancy. Table 3 summarizes some of the main features of the all these approaches.…”

Section: Related Workmentioning

confidence: 99%