This research involves using Semantic Web technologies to enable end user programming. This technology is applicable to any problem that involves user interaction, so can be applied in industries and home use for any task or subject area.

The work involves allowing non-programmers to model complex problems visually and without having to use programming languages. Information is created in a visual tree using an Ontology editor, the information is then transformed, and all calculations performed. Further transformations can be performed into any programming language or open standard information representation language, and this can be displayed on the web. This approach can be described as 'pipelining', which is explained by Gropp (2003) using the example of a project to convert Geography Markup Language (GML) to Scalable Vector Graphics (SVG). SVG is explained by McKeown and Grimson (2000). Pipelining is also core to XML (eXtensible Markup Language) and XForms technologies (Bruchez, 2006), which are explained in this thesis. Pipelines are important for translation and Meta Programming techniques I use as they apply one program to the results of another. Also transformations can be performed between a tree representation and other styles of representation e.g. an interactive CAD style representation, using SVG. A major theme of the research is that of prototyping solutions to the problems raised, using web and other software technologies. These are then referenced from the thesis document to illustrate the solutions discussed.

The additional advantage is that of displaying the expressions in the appropriate context. Crapo et al (2002) explain that visualization helps the modeller to maintain a hierarchy of submodels at different stages of development and to navigate effectively between them, this is my reason for breaking down the models into a tree structure.

Semantic Web research has been developed from the work of Tim Berners-Lee (1997). Uschold (2003) defines the Semantic Web as being machine usable and associated with more meaning. Semantic web technologies and the use of agents and ontologies are explained by Hendler (2001) and Uschold who explains that "In order to carry out their required tasks, intelligent agents must communicate and understand meaning".

Meta programming is the writing of programs that write or manipulate other programs (or themselves) as their data. The idea behind this technique is that instead of writing programs to do a task a person needs the program for, the meta program developer creates an environment which all domain experts, in this and similar fields, can use to create their own solutions. The developer then only needs to maintain and improve this programming environment, and can concentrate on this task; the domain expert can concentrate on solving the problem at hand without having to ask the developer to create the code on his or her behalf. This can prevent problems of misunderstanding, delay, and expense that often result from communication of difficult concepts between people who are experts in different areas (domain expert and programming expert).

References

Berners-Lee, T., Fischetti, M., 1997. Weaving the Web. Harper San Francisco; Paperback: ISBN:006251587X

Bruchez, E, 2006. XForms: an Alternative to Ajax?. In: XTech 2006: Building Web 2.0 16-19 May 2006, Amsterdam, The Netherlands.

Crapo, A. W., Waisel, L. B., Wallace, W. A., Willemain, T. R., 2002. Visualization and Modelling for Intelligent Systems. In: C. T. Leondes, ed. Intelligent Systems: Technology and Applications, Volume I Implementation Techniques, 2002 pp 53-85.

Gropp, E., 2003. Accelerating SVG Transformations with Pipelines. In: SVG Open 2003 - Conference and Exhibition 2nd Annual Conference on Scalable Vector Graphics - Vancouver, Canada.

Hendler, J., 2001. Agents and the Semantic Web. IEEE Intelligent Systems Journal.

McKeown, J., Grimson, J., 2000. SVG: putting XML in the picture In: XML Europe 2000 Paris France.

Uschold, M., 2003. Where are the semantics in the semantic web? AI Magazine Vol 24 (3) pp 25-36.