Management of ontologies and models built from them is essential for understanding and managing complicated systems. This also improves the likelyhood for projects to be successful. Breaking down a complex systems engineering project into modular sub systems ensures that if project failure looks too likely it is possible to backtrack one step, rather than rstart again or give up the whole project. This also educates and enables systems design and systems thinking. This modularity can be achieved by transforming engineering and business knowledge into program code in collaborative computer systems, and representing and visualising the resultant system and management of this to all domain experts. This makes possible translation (both for communication amongst collaborating people, and amongst computing models and program translation). This translation is possible from the business and engineering focus of the end-users to the software developers and in both directions.

This translation can be enabled by encouraging end user visual programming so that the expertise of domain experts in modelling problems can be applied. Semantic Web modelling tools are needed to illustrate benefits this technology can provide to industry, as outlined at the Jena User Conference 2006 in Bristol UK. Enabling, providing and supporting staff to use Semantic Web and Web 2.0 technologies can lower costs, improve collaboration, and improve staff satisfaction and retention. This enables a much faster iterative process of model development, visualisation and rework, leading to more effective process modelling. Such techniques can be used for managing and visualising workflows, which could involve complicated scheduling, sequencing, and iteration. Semantic Web and Web 2.0 are related, as Berners-Lee’s intention in the early development of Semantic Web technologies was for pages to be interactive. This opens up software development to communities and individuals outside this profession and even extends it beyond existing open source communities. Software applications are needed that allow users with little software knowledge to edit and update ontologies themselves. This harneses collective community resources and effort. So this kind of technology and these techniques are certainly appropriate to collaborative modelling, and sharing of knowledge amongst domain experts. Representation and visualisation of all stages in collaborative modelling and all parts of models makes it possible to determine if models and view(s) of ithis are correct and useful, and so assists with this sharing of peoples’ knowledge to solve problems.

A problem can be visualised for collaboration as diagrams, and then translated from an abstract view that humans understand to models and code for computers. There is a need for end-user programming by designers using diagrams and models. Diagrams are better than words for representing geometry. This links with the theme through this PhD of translating from an abstract to a specific representation understood. The distinction between abstract and specific models gradual and subtle unlike the distinction between classes and objects for object oriented programming. To achieve the translation it’s necessary to enable translation from ontologies and Semantic Web information to diagrammatic information and vice versa.

Ontologies, models and collaboration can be used to assist in solving terminology problems. For complex modelling it’s necessary to provide a generic model/system creator that can have the capability of translating abstract ideas into models. This provides a translation stage that closes gaps between ideas and models. A classification scheme or ontology is necessary to make communication as precise as achievable. Ontology/ies can be used to define terms and relationships and these extended for application to particular models. Such ontology/ies can also be used to help non-specialists understand the terminology of a particular type of work, and so ease collaboration amongst people with very different skills and backgrounds. For this project a web linked modelling environment was constructed that automatically translated an ontology representation to models, and performed calculations, and assisted with decision support.

It become important to research collaborative modelling and visualisation, because of the business trend towards global markets and decentralised organisations. This research aims to benefit 2 types of modeller.

A system for modellers to develop models from shared information (process architecture and models repository); such model builders will be able to create process models for :-

Model users who may customise models but will not need to create them.

In reality, an individual may be in either, or both, categories depending on their interests and skills. In effect this involves production of systems to create systems and/or models.

This methodology assists with my PhD research objectives of ease of use and sharing of information. Use of open standards for visualising and representing information makes it practicle to enable searches that interpret the semantics of information and so can follow all relationships between things. To test this methodology web based example models were created.

Peter Hale – I am a Researcher in the final year of my PhD. I specialise in devising ways of making it easier for users to create their …—Research-Methodology&id=2708738
Business process modelling