Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review
Knowledge diagrams represent all substantial aspects of information involved in designing, codifying and representing company or domain knowledge assets. The chapter considers not only design but also the use of such maps including but not limited to facilitation of learning; eliciting, capturing, archiving and using expert knowledge; planning instruction; assessment of deep understandings; research planning; collaborative knowledge modelling; creation of knowledge portfolios; curriculum design; e-learning; and administrative and strategic planning and monitoring. Knowledge diagrams belong to the multidisciplinary fields of knowledge engineering (KE) and knowledge management (KM), bringing in concepts and methods from several computer science domains such as artificial intelligence, databases, expert systems, decision support systems and information systems. KE is strongly related to cognitive and social sciences and socio-cognitive engineering, where knowledge is considered to be produced by humans and structured according to mutual understanding of how human reasoning and logic work. Currently, KE is related to the construction of shared conceptual frameworks, often presented visually as knowledge diagrams. The chapter describes cognitive aspects of knowledge diagram design, using ideas coined by Gestalt psychology, involving good form and aesthetic perception. It is aimed at all researchers and practitioners interested in the use of knowledge diagrams, as outlined above.
Original language | English |
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Title of host publication | Knowledge Management, Arts, and Humanities |
Subtitle of host publication | Interdisciplinary Approaches and the Benefits of Collaboration |
Publisher | Springer Nature |
Pages | 97-117 |
Number of pages | 21 |
ISBN (Electronic) | 978-3-030-10922-6 |
ISBN (Print) | 978-3-030-10921-9 |
DOIs | |
State | Published - 1 Jan 2019 |
Name | Knowledge Management and Organizational Learning |
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Publisher | Springer |
Volume | 7 |
ISSN (Electronic) | 2199-8663 |
ID: 45441223