Several data models have been defined for enabling information interoperability during the process plant life cycle. The data models differ in details and their scopes are different, making it difficult to compare and evaluate them. While the importance of using commonly agreed standard data models has widely been accepted, the diversity of the models hinders companies from choosing between them when implementing e.g. data warehouses. In many cases this leads to implementing in-house, non-standard models. In this paper, criteria for evaluating and comparing data models are introduced. Five data models developed by international or national organizations are introduced and compared, based on the criteria.
|Frontiers in Artificial Intelligence and Applications
|13th ISPE International conference on concurrent engineering: research and applications
|18/09/06 → 22/09/06
- Plant modeling
- ISO 15926