Home |  ENGLISH |  Kontakt |  Impressum |  Anmelden |  KIT

Inproceedings1254

Aus Aifbportal

Wechseln zu: Navigation, Suche

(This page contains COinS metadata)

ONTOCOM: A Cost Estimation Model for Ontology Engineering


Elena Paslaru Bontas, Christoph TempichYork Sure



Published: 2006
Herausgeber: I. Cruz and others
Buchtitel: Proceedings of the 5th International Semantic Web Conference (ISWC 2006)
Ausgabe: 4273
Reihe: Lecture Notes in Computer Science (LNCS)
Seiten: 625--639
Verlag: Springer-Verlag Berlin Heidelberg
Referierte Veröffentlichung
BibTeX

Kurzfassung
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.

VG Wort-Seiten: 28
Weitere Informationen unter: LinkLinkLink

Projekt

SEKT



Forschungsgruppe

Wissensmanagement


Forschungsgebiet
IT-Controlling, Ontologiemodellierungsmethodology, Semantic Web, Ontologiemodellierung, Ontology Engineering, Software Engineering, Kennzahlensysteme, Informationswirtschaft