User Driven Modelling: Translation for Visual End User Programming

Research Theory influencing this Translation Mechanism

The use of the Semantic Web in my thesis is to be a means for open standard representation of information (built on XML), transformation into different representations as required, and for provision of a high level interface as a tool for model creation, and translation to program code. An 'elaborator', is used, this is a translator that converts the diagrammatic representation of the problem into software code. Translations can be performed into any programming or meta-programming language or open standard information representation language, the visualisation of the model created can be displayed on the web. This translation builds on research in program and model transformation. The translation software performs transformations as required between different programming languages and visual model views. This has been prototyped, but it is important to further this research in order to establish a user base, and make the translation generic. Figure 1 shows the process.

Figure 1 - Translation Process

Implementation

Translation Process

This research involves finding alternative ways of representing models, which do not require the user to write code. The intention is to make it easier to interact with and change the models, and to share information with colleagues. The information used in the models resides in an ontology, and from this ontology models can be automatically produced via a recursive translation tool that has been prototyped.

The research for my thesis uses a technique of interpreting information in order to create decision support programs automatically in response to user choices. This technique is then extended for use in the automatic creation of programs in other computer languages and systems. This can be achieved by automated translation of the Vanguard Studio information into other languages. The basis of this is that elaborators are nodes in the tree, which are automatically created and dynamically write objects. This allows the wing box definition to be translated to the decision support system for costing and then to other software such as web pages for further processing or visualization. An open standard semantic editor Protégé created by Stanford University (2007) was used to structure this information into related taxonomies. This ontology holds the definitions of nodes representing information, and calculations to be performed. Taxonomies are created in Protégé for 'Parts', 'Materials', 'Consumables', 'Processes', 'Rates', and 'Tooling' for a prototype costing system. 'Parts' is the core taxonomy. New categories can be produced as required. Domain experts would edit the taxonomies; these experts can specify the relationships of classes and the equations to be used via a visual user interface in Protégé. These relationships are evaluated and translated to produce computer code. Figure 2 illustrates how code is produced from the semantic relationships.

Figure 2 - Translation Process Implementation

This model can be used as it is, or be a template for the generation of a further model(s). An example interface, a section from a model produced automatically, is shown in figure 3. This information is saved using a generic structure based on keys that define all relationships, into a relational database. This enables storage of hierarchical data in a relational database and also allows for separation of information into tables according to category, and the use of SQL (Structured Query Language) to automatically query and structure the information as required. Vanguards' tree based decision support tool Vanguard Studio (2007) reads this information and represents it as colour-coded nodes. The code written for this thesis automatically queries the taxonomies that make up the ontology and links the information as required for the model. The code builds in all the links required for the equations and thus links up information from different taxonomies, the information is colour coded according to which taxonomy it is from. This same code can be reused for any modelling problem, it builds the equations and follows the links to build each equation tree, and attach this to the rest of the tree. The decision support tool can perform calculations and so output results. Figure 3 shows how the decision support tool can automatically construct and represent a branch in the tree, visualize an equation and calculate a result. Red nodes represent processes, green nodes represent the part definition and magenta nodes represent resources. This illustrates how 3 taxonomies have been automatically linked because they are needed in this calculation. In this prototype hundreds of calculations have been related to each other, this example illustrates that 'Area' was also calculated, and that this forms part of the tree for the 'Hand Layup Tool Cleaning Cost', which in turn is passed into other calculations. Hundreds of calculations using information from all the taxonomies are linked as required in this costing example. The time taken to perform the translation from the ontology and to perform all the calculations is a less than a second.