%0 Journal Article %1 lethbridge97 %A Lethbridge, Timothy C. %D 1997 %J Int. J. of Software Engineering & Knowledge Engineering %K ontology metrics %T Metrics for Concept-Oriented Knowledge Bases %U http://www.cs.toronto.edu/~nernst/papers/lethbridge-Metrics.pdf %X Metrics are widely researched and used in software engineering; however there is little analogous work in the field of knowledge engineering. In other words, there are no widely-known metrics that the developers of knowledge bases can use to monitor and improve their work. In this paper we adapt the GQM (Goals-Questions-Metrics ) methodology that is used to select and develop software metrics. We use the methodology to develop a series of metrics that measure the size and complexity of concept-oriented knowledge bases. Two of the metrics measure raw size; seven measure various aspects of complexity on scales of 0 to 1, and are shown to be largely independent of each other. The remaining three are compound metrics that combine aspects of the other nine in an attempt to measure the overall ?difficulty? or ?complexity? of a knowledge base. The metrics have been implemented and tested in the context of a knowledge management system called CODE4.

@article{lethbridge97, abstract = {Metrics are widely researched and used in software engineering; however there is little analogous work in the field of knowledge engineering. In other words, there are no widely-known metrics that the developers of knowledge bases can use to monitor and improve their work. In this paper we adapt the GQM (Goals-Questions-Metrics ) methodology that is used to select and develop software metrics. We use the methodology to develop a series of metrics that measure the size and complexity of concept-oriented knowledge bases. Two of the metrics measure raw size; seven measure various aspects of complexity on scales of 0 to 1, and are shown to be largely independent of each other. The remaining three are compound metrics that combine aspects of the other nine in an attempt to measure the overall ?difficulty? or ?complexity? of a knowledge base. The metrics have been implemented and tested in the context of a knowledge management system called CODE4.}, added-at = {2006-03-24T16:34:33.000+0100}, author = {Lethbridge, Timothy C.}, biburl = {https://www.bibsonomy.org/bibtex/2e65ddf0778ff63fcebca3ecbdef87b82/neilernst}, citeulike-article-id = {121764}, description = {sdasda}, interhash = {3225600736c9d87ecafef82491b0c167}, intrahash = {e65ddf0778ff63fcebca3ecbdef87b82}, journal = {Int. J. of Software Engineering \& Knowledge Engineering}, keywords = {ontology metrics}, priority = {2}, timestamp = {2006-03-24T16:34:33.000+0100}, title = {Metrics for {C}oncept-{O}riented {K}nowledge {B}ases}, url = {http://www.cs.toronto.edu/~nernst/papers/lethbridge-Metrics.pdf}, year = 1997 }