(161b) Ontomodel: Ontology Based Mathematical Model Solving Using The Semantic Web
In previous work done by Venkatasubramanian et al , a framework based on an ontological approach for mathematical knowledge modeling in process operations using the semantic web was discussed. The framework separated the declarative and procedural components of mathematical model creation, manipulation and solving. The declarative part consisted of two main ontologies, one which represents the details of a model (Model Definition) such as the model equations and state variables, and the other which represents the details of its use in modeling a specific processing step (Model Use). Mathematica 5.2 was the solver package chosen for this framework because of its ease of interaction with Java and ontologies. The procedural component consisted of a Java based engine that constructed model solving statements in Mathematica syntax, invoked Mathematica to solve the equations and retrieved results that were either shown on a GUI or stored back in the ontology. The advantages of this approach are the transparency and flexibility in creating, manipulating and solving a model without knowing the syntax of a particular solver.
In this paper, we present OntoMODEL, a repository for unit operation models that has been developed for use with the framework described above. The use of the repository is facilitated by a Java based GUI which allows the user to select a model, specifying required parameter, invoke the engine and display results. The main advantage of OntoModel over existing model solving or process simulation software packages is that the model creation and manipulation are transparent to the user. For example, if a user wants to add equation(s) to an existing model, in existing applications, this would require knowledge of the programming language in which the source code of that application was written. However, with OntoModel this exercise is intuitive and easy to implement. The user creates the additional equation in a equation editor that supports MathML, such as WebEq, and copies it into the desired model in the model definition ontology. The GUI automatically creates fields for specifying the initial values of the newly added variables. The engine's invocation of the solver and analysis of results are not affected. Thus, the power of OntoModel lies in its flexibility and user friendliness. In this paper, various features of OntoModel are illustrated with the help of examples.
Reference:  Venkat Venkatasubramanian; Chunhua Zhao; Girish Joglekar; Ankur Jain; Leaelaf Hailemariam; Pradeep Suresh; Pavankumar Akkisetty; Ken Morris; G.V. Reklaitis, Ontological informatics infrastructure for pharmaceutical product development and manufacturing, Computers and Chemical Engineering 30(2006) 1482?1496