How can Diagrammatic Conceptual Modelling Support Knowledge Management?
Traditionally, venues that are publishing Knowledge Management research have been separating concerns between two viewpoints that rarely converge into holistic approaches: one is the tradition of Artificial Intelligence research, where "Knowledge Management" is often employed as an umbrella term in relation to a variety of semantic technologies, knowledge representation and knowledge discovery techniques; the other viewpoint is a specialisation of "intangible asset management", dealing with the business value and the pragmatics of organisational knowledge. Knowledge Management Systems are a catalyst for bridging such complementary perspectives and Design Science artefacts must be employed to facilitate alignments between these viewpoints, specifically between humanoriented and machine-oriented knowledge representations. Motivated by this desideratum and driven by project-based experience, the paper at hand advocates a key role of Diagrammatic Conceptual Modelling methods in enriching the seminal SECI Knowledge Conversion spiral, to the aim of opening it towards Knowledge Management Systems that could not have been envisioned at the time of Nonaka's original SECI proposal, but can now benefit from state-of-the-art semantics-driven practices. By hybridising the SECI model with a machine-oriented Knowledge Distilling cycle, an extended SECI spiral variant is proposed and analysed in the paper, as a reflection on project-based deployments and experience.
Top- Karagiannis, Dimitris
- Buchmann, Robert
- Walch, Michael
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
25th European Cenference on Information Systems, ECIS 2017 |
Divisions |
Knowledge Engineering |
Subjects |
Software Engineering Kuenstliche Intelligenz |
Event Location |
Guimarães, Portugal |
Event Type |
Conference |
Event Dates |
5-10 June 2017 |
Series Name |
Proceedings of the 25th European Conference on Information Systems (ECIS) |
ISSN/ISBN |
ISBN 978-989-20-7655-3 |
Page Range |
pp. 1568-1583 |
Date |
June 2017 |
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