RMIT University
Browse

A priori ontology modularisation in ill-defined domains

conference contribution
posted on 2024-10-31, 19:33 authored by Dhavalkumar Thakker, Vania Dimitrova, Lydia Lau, Ronald Denaux, Stan Karanasios, Fan Yang-Turner
Modularisation is crucial to create re-usable and manageable ontologies. The modularisation is usually performed a posteriori, i.e. after the ontology is developed, and has been applied mainly to well-structured domains. With the increasing popularity of social media, Semantic web technologies are moving towards ill-defined domains that involve cognitively-complex processes carried out by humans and require tacit knowledge (e.g. decisionmaking, sensemaking, interpersonal communication, negotiating, motivating). In such domains, a priori modularisation can enable ontology creation to handle the complexity and the dynamic nature of knowledge. This paper outlines an a priori modularisation methodology for multi-layered development of ontologies in ill-defined domains, including an upper ontology layer, high-level and reusable domain layers, and case-specific layers. The methodology is being applied in several use cases in two EU projects - Dicode and ImREAL.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1145/2063518.2063541
  2. 2.
    ISBN - Is published in 9781450306218 (urn:isbn:9781450306218)

Start page

167

End page

170

Total pages

4

Outlet

Proceedings of the 7th International Conference on Semantic Systems

Editors

C. Ghidini, A.-C. Ngonga Ngomo, S. Lindstaedt and T. Pellegrini

Name of conference

I-SEMANTICS 2011

Publisher

Association for Computing Machinery

Place published

New York, United States

Start date

2011-09-07

End date

2011-09-09

Language

English

Copyright

© 2011 Assocation for Computing Machinery

Former Identifier

2006060944

Esploro creation date

2020-06-22

Fedora creation date

2016-04-21

Usage metrics

    Scholarly Works

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC