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ONTOCOM: A Cost Estimation Model for Ontology Engineering

  • Elena Paslaru Bontas Simperl
  • Christoph Tempich
  • York Sure
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4273)

Abstract

The technical challenges associated with the development and deployment of ontologies have been subject to a considerable number of research initiatives since the beginning of the nineties. The economical aspects of these processes are, however, still poorly exploited, impeding the dissemination of ontology-driven technologies beyond the boundaries of the academic community. This paper aims at contributing to the alleviation of this situation by proposing ONTOCOM (Ontology Cost Model), a model to predict the costs arising in ontology engineering processes. We introduce a methodology to generate a cost model adapted to a particular ontology development strategy, and an inventory of cost drivers which influence the amount of effort invested in activities performed during an ontology life cycle. We further present the results of the model validation procedure, which covered an expert-driven evaluation and a statistical calibration on 36 data points collected from real-world projects. The validation revealed that ontology engineering processes have a high learning rate, indicating that the building of very large ontologies is feasible from an economic point of view. Moreover, the complexity of ontology evaluation, domain analysis and conceptualization activities proved to have a major impact on the final ontology engineering process duration.

Keywords

Cost Driver Ontology Development Ontology Engineering Engineering Team Competency Question 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Elena Paslaru Bontas Simperl
    • 1
  • Christoph Tempich
    • 2
  • York Sure
    • 2
  1. 1.Free University of BerlinBerlinGermany
  2. 2.Institute AIFBUniversity of KarlsruheKarlsruheGermany

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