Abstract
We explored how the intended purpose of a knowledge model can influence the
modelling process and in particular, how it impacts on the choice points of the underlying
modelling methodology. We introduce a classification of knowledge models according to their
intended scope, expressiveness and degree of acceptance. As a result, we aim to define critical
success factors of methodologies for ontologies that are built by domain experts and that can be
used as a basis for knowledge enabled (software) systems
| Original language | English |
|---|---|
| Title of host publication | I-Know 06, 6. Internationale Wissenmanagement-Konferenz Graz |
| Number of pages | 8 |
| Publication status | Published - Sept 2006 |
Fields of science
- 102001 Artificial intelligence
- 102006 Computer supported cooperative work (CSCW)
- 102010 Database systems
- 102014 Information design
- 102015 Information systems
- 102016 IT security
- 102028 Knowledge engineering
- 102019 Machine learning
- 102022 Software development
- 102025 Distributed systems
- 502007 E-commerce
- 505002 Data protection
- 506002 E-government
- 509018 Knowledge management
- 202007 Computer integrated manufacturing (CIM)
- 102033 Data mining
- 102035 Data science
