Research

Data-driven or background knowledge ontology development


Reference:

Tonkin, E. and Pfeiffer, H. D., 2010. Data-driven or background knowledge ontology development. In: International Conference on Knowledge Management (ICKM), 2010-10-22 - 2010-10-23, Pittsburgh.

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    Abstract

    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.

    Details

    Item Type Conference or Workshop Items (Paper)
    CreatorsTonkin, E.and Pfeiffer, H. D.
    Research CentresUKOLN
    RefereedYes
    StatusPublished
    ID Code20523

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