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Knowledge Elicitation Plug-in for Protege: Card Sorting and Laddering




Published: 2006 September
Herausgeber: R. Mizoguchi, Z. Shi, and F. Giunchiglia

Buchtitel: Asian Semantic Web Conference (ASWC'06)
Ausgabe: 4185
Nummer: LNCS 4185
Der Datenwert „LNCS“ kann einem Attribut des Datentyps Zahl nicht zugeordnet werden sondern bspw. der Datenwert „4185“.

Reihe: LNCS
Seiten: 552-565
Verlag: Springer-Verlag Berlin Heidelberg
Erscheinungsort: Beijing, China

Referierte Veröffentlichung

BibTeX

Kurzfassung
Ontologies have been widely accepted as the primary method of representing knowledge in the Semantic Web. Knowledge Elicitation (KE) is usually one of the first steps in building ontologies. A number of ontology editors such as Protege have been developed to assist users in building ontologies efficiently. However, traditional KE techniques, such as card sorting and laddering, are not yet supported, but performed manually and outside of such tools. In this paper we present a methodology and a corresponding plug-in for Protege that allows graphical ellicitation knowledge from documents using card sorting and laddering approaches. Our aim is to seamlessly integrate the KE techniques into the ontology building process to make ontology building more efficient and less error-prone. As a side-effect the persistent storage of card sorting and laddering results allows for later traceability of ontology development. KE largely depends on user interaction with the plug-in, therefore we employed user-centred design principles to capture requirements. After implementation, the plug-in was evaluated thoroughly against the requirements. The evaluation shows that this KE plug-in meets many of the user's expectations and indeed saves them considerable time when building ontologies.

ISBN: 3-540-38329-8
Download: Media:2006_1243_Wang_Knowledge_Elici_1.pdf

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Forschungsgruppe

Wissensmanagement


Forschungsgebiet

Semantic Web, Web Science, Ontologiemodellierung