(441b) The Role of Ontologies in Process Modelling
AIChE Annual Meeting
2013
2013 AIChE Annual Meeting
Computing and Systems Technology Division
Perspectives on Information Management and Intelligent Systems
Wednesday, November 6, 2013 - 8:55am to 9:20am
I want to convince the community that thinking and consequently working with ontologies is simply good practice because it imposes a thorough analysis of the problem's structure and thinking carefully through the problem-relevant basics. For process models this is the physics associated with
- the process structure
- the model's granularity
- the conservation principles
- the transport behaviour -- usually an event-dynamic assumption applied to a dynamic transport system
- the kinetics -- the isolated behaviour of the reactants
- the relation between the conserved quantities and the driving forces, the geometry, the material properties
- the assumed equilibria
Process ontologies form well-structured frameworks that build layers on layers, strata on strata defining the basic framework to which the process models must adhere.
Using mechanistic-based ontologies leads to process models that adhere to the basic laws. When used in its basic form, any converged numerical simulation will satisfy the basic balance equations thus providing a level of correctness, which overall is only limited by the validity of the structuring process leading to a certain level of granularity of the the model. Latter can be interpreted as the resolution with which the process is depicted.
The concept extents into the software-internal representation, the way the models are being stored and consequently handled during the process of preparing the computational tasks to be solved in association with a technical problem. The concept of ontologies provides a very useful thinking pattern that may even be considered essential to the design of tools and handling of data in the computational engineering domain.
The objective is always the same: it is the respective basics that are laid down first through a careful analysis of the state problem. Once verified it is applied and results conform resulting instantiated model or software components.