An Ontology for Ontology Metrics: Creating a Shared Understanding of Measurable Attributes for Humans and Machines
2022 (English)In: Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD, SciTePress, 2022, p. 193-199Conference paper, Published paper (Refereed)
Abstract [en]
Measuring ontologies using metrics requires specialized software. While the past years saw various developments regarding tools and frameworks, these efforts mainly stayed isolated in their applied assessments. A paper measuring an ontology using the oQual framework is hardly comparable to one that applies the metrics from OntoQA. First, the performed calculations are often bound to the used tools, and second, the correct interpretation of ontology metrics requires a deep understanding of their measured aspects. Our research tackles these challenges by providing an ontology for ontology metrics. This artifact (A.) collects the various proposed ontology measurement frameworks with human-readable descriptions. It lets users quickly inform themselves on the assessments and aspects one can measure. (B) it formalizes the metric calculations. The framework metrics are connected to shared measurable elements, homogenizing the notations and languages. At last, (C.) the ontology is the backbone of the newly developed NEOntometrics application. The software uses the formalized metric descriptions to set up the calculations for the various frameworks. We believe our research can break the silos of different measurements, enable knowledge engineers to calculate various metrics quickly, and researchers to put new measurements into use through simple adaption of the metric ontology.
Place, publisher, year, edition, pages
SciTePress, 2022. p. 193-199
Keywords [en]
NEOntometrics, Ontology Metrics, Ontology Quality, OntoMetrics, OWL, Knowledge engineering, Knowledge management, Human-readable, Neontometric, Ontology measurements, Ontology qualities, Ontology's, Ontometric, Shared understanding, Specialized software, Ontology
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-59487DOI: 10.5220/0011551500003335Scopus ID: 2-s2.0-85146198549ISBN: 9789897586149 OAI: oai:DiVA.org:hj-59487DiVA, id: diva2:1740254
Conference
14th International Conference on Knowledge Engineering and Ontology Development, KEOD 2022 as part of 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022, 24 October 2022 through 26 October 2022
2023-02-282023-02-282023-02-28Bibliographically approved