ArticlePloS one2014
Evaluating the Good Ontology Design Guideline (GoodOD) with the ontology quality requirements and evaluation method and metrics (OQuaRE).
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches.Frontiers in pharmacology · 2019Pooled it
- An ontology-driven framework for knowledge representation of digital extortion attacks.Computers in human behavior · 2023Article
- Developing a Dietary Lifestyle Ontology to Improve the Interoperability of Dietary Data: Proof-of-Concept Study.JMIR formative research · 2022Article
- An Ontology-Based Cybersecurity Framework for the Internet of Things.Sensors (Basel, Switzerland) · 2018Article
- Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.JMIR research protocols · 2017Article
- RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource.Journal of biomedical semantics · 2015Article
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Authors and funding
6 authors.
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Abstract
objectiveTo (1) evaluate the GoodOD guideline for ontology development by applying the OQuaRE evaluation method and metrics to the ontology artefacts that were produced by students in a randomized controlled trial, and (2) informally compare the OQuaRE evaluation method with gold standard and competency questions based evaluation methods, respectively.
backgroundIn the last decades many methods for ontology construction and ontology evaluation have been proposed. However, none of them has become a standard and there is no empirical evidence of comparative evaluation of such methods. This paper brings together GoodOD and OQuaRE. GoodOD is a guideline for developing robust ontologies. It was previously evaluated in a randomized controlled trial employing metrics based on gold standard ontologies and competency questions as outcome parameters. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies and has been successfully used for evaluating the quality of ontologies.
methodsIn this paper, we evaluate the effect of training in ontology construction based on the GoodOD guideline within the OQuaRE quality evaluation framework and compare the results with those obtained for the previous studies based on the same data.
resultsOur results show a significant effect of the GoodOD training over developed ontologies by topics: (a) a highly significant effect was detected in three topics from the analysis of the ontologies of untrained and trained students; (b) both positive and negative training effects with respect to the gold standard were found for five topics.
conclusionThe GoodOD guideline had a significant effect over the quality of the ontologies developed. Our results show that GoodOD ontologies can be effectively evaluated using OQuaRE and that OQuaRE is able to provide additional useful information about the quality of the GoodOD ontologies.
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