The development of ontologies for various purposes is now a relatively commonplace process. A number of different approaches towards this aim are evident; empirical methodologies, giving rise to data-driven procedures or self-reflective (innate) methodologies, resulting in artifacts that are based on intellectual background understanding. In this paper, we compare and contrast these approaches through two practical examples, one from a descriptive metadata domain and one from the area of physical computing. Both examples are chosen from domains in which automated extraction of information is a significant use case for the resulting ontology. We identify a relationship within the ontology development process that allies empirical evidence and user judgement to develop user-centred ontologies, either on an individual or collaboratively-focused basis. A qualitative treatment of the characteristics of this type of 'language game' is identified as an ongoing research goal.
|Publication status||Published - 23 Oct 2010|
|Event||International Conference on Knowledge Management (ICKM) - Pittsburgh, USA United States|
Duration: 22 Oct 2010 → 23 Oct 2010
|Conference||International Conference on Knowledge Management (ICKM)|
|Country||USA United States|
|Period||22/10/10 → 23/10/10|
Tonkin, E., & Pfeiffer, H. D. (2010). Data-driven or background knowledge ontology development. Paper presented at International Conference on Knowledge Management (ICKM), Pittsburgh, USA United States.