Keywords

Knowledge-Bundle Builder, Research Studies, research development

Abstract

Researchers struggle to manage vast amounts of data coming from hundreds of sources in online repositories. To successfully conduct research studies, researchers need to find, retrieve, filter, extract, integrate, organize, and share information in a timely and high-precision manner. Active conceptual modeling for learning can give researchers the tools they need to perform their tasks in a more efficient, user-friendly, and computer-supported way. The idea is to create “knowledge bundles” (KBs), which are conceptual-model representations of organized information superimposed over a collection of source documents. A “knowledgebundle builder” (KBB) helps researchers develop KBs in a synergistic and incremental manner and is a manifestation of learning in terms of its semi-automatic construction of KBs. An implemented KBB prototype shows both the feasibility of the idea and the opportunities for further research and development.

Original Publication Citation

David W. Embley, Stephen W. Liddle, Deryle W. Lonsdale, Aaron Stewart, and Cui Tao. (2010). KBB: A Knowledge-Bundle Builder for Research Studies; In: (J. Trujillo, G. Dobbie, H.Kangassalo, S. Hartmann, M. Kirchberg, M. Rossi, I. Reinhartz-Berger, E. Zimányi, & F.Frasincar, Eds) Advances in Conceptual Modeling---Applications and Challenges; Proceedingsof the ER2010 Workshops ACM-L, CMLSA, CMS, DE@ER, FP-UML, SeCoGIS, WISM;Lecture Notes in Computer Science 6413, Springer-Verlag. Berlin; pp. 148-159; ISBN 978-3-642-16384-5

Document Type

Conference Paper

Publication Date

2010

Publisher

Springer

Language

English

College

Humanities

Department

Linguistics

University Standing at Time of Publication

Associate Professor

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Linguistics Commons

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