Sökning: onr:"swepub:oai:DiVA.org:oru-53260" >
Facilitating Busine...
Facilitating Business Process Development via a Process Characterizing Model
-
- Gao, Shang, 1982- (författare)
- Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway
-
- Krogstie, John (författare)
- Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway
-
(creator_code:org_t)
- IEEE Computer Society, 2008
- 2008
- Engelska.
-
Ingår i: Proceedings of the 2008 International Symposium on Knowledge Acquisition and Modeling. - : IEEE Computer Society. - 9780769534886 ; , s. 239-245
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- Since the business environment is getting increasingly dynamic and complex, the relevant process models in the environment are becoming more complicated. This might easily confuse business experts and lead them to misunderstand the models. Business experts are expecting a simple way to communicate and collaborate with the model developers during business process development and use. Today, enterprise modelling is primarily focusing on goal modeling, resource modeling and process modeling. We propose an additional type of model, which is called business process characterizing model. This model can not only facilitate the efficient communication between business experts and model developers, but also offer an opportunity to handle emergent processes and capture dynamic knowledge and variability.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
Nyckelord
- Mobile Worker
- Business Process Characterizing Model
- Process Modeling
- Datavetenskap
- Computer Science
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
Hitta via bibliotek
Till lärosätets databas