Dependencies Between Modularity Metrics Towards Improved Modules

Conference paper

DOI: 10.1007/978-3-319-49004-5_26

Volume 10024 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Khan Z.C., Keet C.M. (2016) Dependencies Between Modularity Metrics Towards Improved Modules. In: Blomqvist E., Ciancarini P., Poggi F., Vitali F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science, vol 10024. Springer, Cham

Abstract

Recent years have seen many advances in ontology modularisation. This has made it difficult to determine whether a module is actually a good module; it is unclear which metrics should be considered. The few existing works on evaluation metrics focus on only some metrics that suit the modularisation technique, and there is not always a quantitative approach to calculate them. Overall, the metrics are not comprehensive enough to apply to a variety of modules and it is unclear which metrics fare well with particular types of ontology modules. To address this, we create a comprehensive list of module evaluation metrics with quantitative measures. These measures were implemented in the new Tool for Ontology Module Metrics (TOMM) which was then used in a testbed to test these metrics with existing modules. The results obtained, in turn, uncovered which metrics fare well with which module types, i.e., which metrics need to be measured to determine whether a module of some type is a ‘good’ module.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Cape TownCape TownSouth Africa
  2. 2.Council for Scientific and Industrial ResearchPretoriaSouth Africa