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Using a Topic Grid and semantic Wikis for ontology-based distributed knowledge management in enterprise software developement processes
Paper, by Axel Korthaus and Martin Schader
External Link: ACM record
Enterprise software development is a very knowledgeintensive process. Modern component-based application development organizations often require collaboration of several stakeholders distributed between different sites. To support developers in performing their tasks, suitable knowledge management tools are required that are able to leverage semantics. Recent developments in the context of the Semantic Web and ontologies including technologies such as Topic Maps or RDF/OWL show potential to address those issues. In this paper, we present an architecture for a distributed knowledge management information system that uses Topic Maps in the background and Semantic Wikis as front end for developers to document and access relevant software development knowledge. The backbone is a Topic Map application infrastructure (called “Topic Grid” in the following) allowing transparent, node-spanning access to different Topic Maps distributed in a network.
Authors
Axel Korthaus
http://sky.scitech.qut.edu.au/~korthaus/
Axel is author of A distributed Topic Map.. , Using a Topic Grid and.. , Creating a Java- and.. , Creating a topic map query.. , and A distributed knowledge.. .
Martin Schader
No contact information available.
Martin is author of A distributed Topic Map.. and Using a Topic Grid and.. .
This publication is cited in the following publication
As a former information scientist, I am fascinated since 1999 by the capabilities for building Topic Maps-based knowledge systems having the potential to augment human mind. One can model arbitrary knowledge organization systems, deal with semantic heterogeneity, collocate all facts about one subject in one logical place, and with TMQL have semantic retrieval on federated semantic networks. Therefore I expect bright prospects for business concepts building on the exchange of such knowledge snippets via semantic knowledge services.
