Methodological guidelines for reusing general ontologies

Fernández-López, M. and Gómez-Pérez, A. and Suárez-Figueroa, Mari Carmen (2013). Methodological guidelines for reusing general ontologies. "Data & Knowledge Engineering", v. 86 (n. null); pp. 242-275. ISSN 0169-023X.


Title: Methodological guidelines for reusing general ontologies
  • Fernández-López, M.
  • Gómez-Pérez, A.
  • Suárez-Figueroa, Mari Carmen
Item Type: Article
Título de Revista/Publicación: Data & Knowledge Engineering
Date: July 2013
ISSN: 0169-023X
Volume: 86
Freetext Keywords: General ontology -- Time ontology -- Mereology -- Ontology reuse -- Ontology methodological development -- Formal concept analysis
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Currently, there is a great deal of well-founded explicit knowledge formalizing general notions, such as time concepts and the part_of relation. Yet, it is often the case that instead of reusing ontologies that implement such notions (the so-called general ontologies), engineers create procedural programs that implicitly implement this knowledge. They do not save time and code by reusing explicit knowledge, and devote effort to solve problems that other people have already adequately solved. Consequently, we have developed a methodology that helps engineers to: (a) identify the type of general ontology to be reused; (b) find out which axioms and definitions should be reused; (c) make a decision, using formal concept analysis, on what general ontology is going to be reused; and (d) adapt and integrate the selected general ontology in the domain ontology to be developed. To illustrate our approach we have employed use-cases. For each use case, we provide a set of heuristics with examples. Each of these heuristics has been tested in either OWL or Prolog. Our methodology has been applied to develop a pharmaceutical product ontology. Additionally, we have carried out a controlled experiment with graduated students doing a MCs in Artificial Intelligence. This experiment has yielded some interesting findings concerning what kind of features the future extensions of the methodology should have.

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Item ID: 26164
DC Identifier:
OAI Identifier:
DOI: 10.1016/j.datak.2013.03.006
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 05 Jun 2014 09:48
Last Modified: 04 Dec 2017 10:46
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