Software Metrics: Progress after 25 Years?
IEEE Software
Journal of Biomedical Informatics
An analysis of collaborative patterns in large-scale ontology development projects
Proceedings of the sixth international conference on Knowledge capture
Extraction and analysis of the structure of labels in biomedical ontologies
Proceedings of the 2nd international workshop on Managing interoperability and compleXity in health systems
Commentary: State of the art and open challenges in community-driven knowledge curation
Journal of Biomedical Informatics
TRAK ontology: Defining standard care for the rehabilitation of knee conditions
Journal of Biomedical Informatics
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In this paper we explore the measurement of activity in ontology projects as an aspect of community ontology building. When choosing whether to use an ontology or whether to participate in its development, having some knowledge of how actively that ontology is developed is an important issue. Our knowledge of biology grows and changes and an ontology must adapt to keep pace with those changes and also adapt with respect to other ontologies and organisational principles. In essence, we need to know if there is an 'active' community involved with a project or whether a given ontology is inactive or moribund. We explore the use of additions, deletions and changes to ontology files, the regularity and frequency of releases, and the number of ontology repository updates to an ontology as the basis for measuring activity in an ontology. We present our results of this study, which show a dramatic range of activity across some of the more prominent community ontologies, illustrating very active and mature efforts through to those which appear to have become dormant for a number of possible reasons. We show that global activity within the community has remained at a similar level over the last 2years. Measuring additions, deletions and changes, together with release frequency, appear to be useful metrics of activity and useful pointers towards future behaviour. Measuring who is making edits to ontologies is harder to capture; this raises issues of record keeping in ontology projects and in micro-credit, although we have identified one ontologist that appears influential across many community efforts; a Super-Ontologist. We also discuss confounding factors in our activity metric and discuss how it can be improved and adopted as an assessment criterion for community ontology development. Overall, we show that it is possible to objectively measure the activity in an ontology and to make some prediction about future activity.