RT Journal Article
T1 Ontology fixing by using software engineering technology
A1 Roldán Molina, Gabriela R.
A1 Méndez Reboredo, José Ramón
A1 Yevseyeva, Iryna
A1 Basto Fernandes, Vitor
K1 1203.04 Inteligencia Artificial
K1 1203.11 Logicales de Ordenadores
K1 1203.17 Informática
AB This paper presents OntologyFixer, a web-based tool that supports a methodology to build, assess, and improve the quality of ontology web language (OWL) ontologies. Using our software, knowledge engineers are able to fix low-quality OWL ontologies (such as those created from natural language documents using ontology learning processes). The fixing process is guided by a set of metrics and fixing mechanisms provided by the tool, and executed primarily through automated changes (inspired by quick fix actions used in the software engineering domain). To evaluate the quality, the tool supports numerical and graphical quality assessments, focusing on ontology content and structure attributes. This tool follows principles, and provides features, typical of scientific software, including user parameter requests, logging, multithreading execution, and experiment repeatability, among others. OntologyFixer architecture takes advantage of model view controller (MVC), strategy, template, and factory design patterns; and decouples graphical user interfaces (GUI) from ontology quality metrics, ontology fixing, and REST (REpresentational State Transfer) API (Application Programming Interface) components (used for pitfall identification, and ontology evaluation). We also separate part of the OntologyFixer functionality into a new package called OntoMetrics, which focuses on the identification of symptoms and the evaluation of the quality of ontologies. Finally, OntologyFixer provides mechanisms to easily develop and integrate new quick fix methods.
PB Applied Sciences
SN 20763417
YR 2020
FD 2020-09-11
LK http://hdl.handle.net/11093/1594
UL http://hdl.handle.net/11093/1594
LA eng
NO Applied Sciences, 10(18): 6328 (2020)
NO Ministerio de Economía, Industria y Competitividad | Ref. TIN2017-84658-C2-1-R
DS Investigo
RD 19-ene-2025