For this research the focus is on combining the development of dynamic software created in response to user actions, with object oriented, rule based and semantic web techniques. This helps solve problems of mismatch of data between object oriented and relational database systems identified by Ambler [1]. The information is highly structured. Visualisation of this structure in order to represent the relationship between things clarifies the semantics. The meaning can be seen not just by the name of each item but also by the relationship of other items to it. It is envisaged that this taxonomy will provide a design costing capability, but the taxonomy and the techniques used to put it together could be re-used for other purposes. Eventually this taxonomy could become part of an overall ontology. At first this would be a light-weight ontology and this could be evaluated for usefulness before deciding on whether it would need to be more structured. Hunter [2] evaluates engineering ontologies and gives examples. Issues involved in visualisation of light weight ontologies are examined by Fluit et al. [3]. An important reason for creation of an open standards central ontology is that it can be accessed by many different applications. The open standard OWL (Web Ontology Language) is explained by Bechhofer and Carroll [4]. Research of others in this field have been investigated Corcho and G'mez-P'rez [5] and Corcho et al. [6], Noy [7].

The approach involves adapting or creating software systems to provide the visual editor for the source tree, and model builders would create a model by editing this. By doing so they would create a generic model for a particular modelling subject. This is enabled by provision of translation software to translate the taxonomy into a decision support and modelling system. The model users could then use this decision support and modelling system to create their models. These models are a more specific subset of the generic model, and could be applied for their own analyses. Current research is on provision of a translation mechanism to convert information or models into other languages (primarily web based), and to visualise this information. This mechanism has been used in projects with two major aerospace companies. Examples of this are shown later in the article.

The alternative approach involves creation of an elaborator that can output code, in various computer languages or a Meta-programming syntax such as metaL [8] or Simkin [9]. The elaborator needs only a few pieces of information. All information other than that dependant on user interaction, including the names of each node and its relationships to other nodes, needs to be held in a standardised data structure, e.g. a database or structured text file(s). A visual interface to this ontology is required so that model builders can maintain and extend it.

Each node (elaborator) needs to be provided with the following pieces of information -

1) A trigger sent as a result of user action. This is a variable containing a list of value(s) dependant on decisions or requests made by the user the last time the user took action. Each time the user makes a request or a decision, this causes the production of a tree or branch to represent this. This trigger variable is passed around the tree or branch as it is created. The interface to enable this is connected to and reads from the ontology.

2) Knowledge of the relationship between this node and its' immediate siblings e.g. parents, children, attributes. So the elaborator knows which other elaborators to send information to, or receive from.

3) Ability to read equations. These would be mathematical descriptions of a calculation that contains terms that are items in the ontology. The equation would be contained within an attribute of a class, e.g. The class Material Cost would have an attribute Material Cost Calculation that holds an equation.

4) Basic rules of syntax for the language of the code to be output.

The way the elaborator finds the information held in 2 and 3 is dependent on the action that is taken in 1. Thus, if a suitable ontology is created the basis of the rules of construction of the code to be created are defined 4, and the user has made choices, the user needs to take no further action and just wait for the necessary code to be output.

The translation mechanism is illustrated on our web site http://www.cems.uwe.ac.uk/~phale/ using a simple example.

1 Ambler, S. W. (2003). The Object-Relational Impedance Mismatch, http://www.agiledata.org/essays/impedanceMismatch.html.

2 Hunter, A. (2002). Engineering Ontologies, http://www.cs.ucl.ac.uk/staff/a.hunter/tradepress/eng.html.

3 Fluit, C., Marta S., Harmelen F. V. (2003). Supporting User Tasks through Visualisation of Light-weight Ontologies, http://www.cs.vu.nl/~frankh/abstracts/OntoHandbook03Viz.html.

4 Bechhofer, S. and Carrol, J. (2004). Parsing owl dl: trees or triples?, Proceedings of the 13th international conference on World Wide Web, NY, USA: 266 - 275.

5 Corcho, O. and G'mez-P'rez, A. (2000). A Roadmap to Ontology Specification Languages, Proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management, Chicago, USA.

6 Corcho, O., Fern?ndez-L?pez, M., G'mez-P'rez, A. (2003). Methodologies, Tools and Languages For Building Ontologies. Where is their Meeting Point?, Data and Knowledge Engineering, 46: 41-64.

7 Noy, N.F. (2004). Semantic Integration: A Survey Of Ontology-Based Approaches. SIGMOD Record, Special Issue on Semantic Integration, 33 (4).