Authors:
C. Maria Keet
1
;
Mari Carmen Suárez-Figueroa
2
and
María Poveda-Villalón
2
Affiliations:
1
University of KwaZulu-Natal, UKZN/CSIR-Meraka Centre for Artificial Intelligence Research and, South Africa
;
2
Universidad Politécnica de Madrid, Spain
Keyword(s):
Ontology Development, Ontology Quality, Pitfall.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
A growing number of ontologies are already available thanks to development initiatives in many different fields. In such ontology developments, developers must tackle a wide range of difficulties and handicaps, which can result in the appearance of anomalies in the resulting ontologies. Therefore, ontology evaluation plays a key role in ontology development projects. OOPS! is an on-line tool that automatically detects pitfalls, considered as potential errors or problems, and thus may help ontology developers to improve their ontologies. To gain insight in the existence of pitfalls and to assess whether there are differences among ontologies developed by novices, a random set of already scanned ontologies, and existing well-known ones, data of 406 OWL ontologies were analysed on OOPS!’s 21 pitfalls, of which 24 ontologies were also examined manually on the detected pitfalls. The various analyses performed show only minor differences between the three sets of ontologies, therewith prov
iding a general landscape of pitfalls in ontologies.
(More)