Resources

This page provides access to many of the teaching materials that will be used in the course of the workshop.

Teaching Materials

Title	Description	Files	Online Slide Show	Contact
Background	Background information to the CommonKADS approach to knowledge engineering and management			Paul Smart
Context Modeling	The analysis of the tasks, the agents that perform them and organizational context in which knowledge processes are embedded.			Tim Clarke
Knowledge Modeling	The CommonKADS Knowledge model details the key knowledge types and structures that we want to represent in our model of the knowledge process.			Paul Smart
Communication Modeling	The modeling of communicative transactions between agents that cooperate to realize a complex reasoning objective.			Paul Smart
Designing Knowledge Systems	Details the design and implementation issues that are typically encountered in knowledge engineering projects.			Paul Smart
Knowledge Representation	An introduction to issues in knowledge representation.			Paul Smart
Rugged KA	An overview of software tools to support the knowledge acquisition and knowledge modeling process.			Steve Swallow
Typical Knowledge Objects	Some typical examples of knowledge constructs.			Nick Milton
KA Session Plan	An example plan for a typical KA session.			Nick Milton
Transcript Analysis	An introduction to transcript analysis.			Nick Milton
KA Techniques	An overview of the range of knowledge acquisition techniques available for the purposes of eliciting knowledge from subject matter experts.			Nick Milton
KA - Problems & Solutions	An overview of the problems associated with eliciting knowledge from domain experts.			Nick Milton
KA & Knowledge Modeling				Nick Milton
KA Glossary	A glossary of terms commonly used in the knowledge acquisition literature.			Nick Milton
Interview Techniques	Some guidelines for good conducting a good interview.			Nick Milton
All Resources	A zip archive of all the above resources

Additional Reading

• Cooke, N. J. (1994). Varieties of Knowledge Elicitation Techniques. International Journal of Human-Computer Studies, Volume 41, Issue 6, p801-849.
• Davenport, T. H. and Prusak, L. (1998). Working Knowledge: How Organisations Manage What They Know. Boston, MA: Harvard Business School Press.
• Milton, N., Shadbolt, N., Cottam, H and Hammersley, M. (1999). Towards a Knowledge Technology for Knowledge Management. International Journal of Human-Computer Studies, Volume 51, Issue 3, p615-641.
• Schreiber. A. Th., Akkermans, Anjewierden, De Hoog, Shadbolt, Van De Velde & Wielinga (2000). Knowledge Engineering and Management. MIT Press.
• Shadbolt, N.R. and Burton, A. M. (1995). Knowledge Elicitation: A Systematic Approach. In Evaluation of Human Work: A Practical Ergonomics Methodology, 2nd and Revised Edition, Wilson, J.R. and Corlett, E. (eds.). London: Taylor and Francis.
• Shadbolt, N. R. and Milton, N. (1999). From Knowledge Engineering to Knowledge Management, British Journal of Management, Volume 10, Issue 4, p309-322.
• Chi, M. H., Glaser, R. and Farr, M. (Eds.) (1988). The Nature of Expertise. Hillsdale, NJ: Lawrence Erlbaum Associates.
• Hayes-Roth, F., Waterman, D. and Lenat, D. (Eds.) (1983). Building Expert Systems. Reading, MA: Addison-Wesley.
• Hoffman, R., Shadbolt, N. R., Burton, A. M. and Klein, G. (1995) Eliciting Knowledge from Experts: A Methodological Analysis. Organisational Behavior and Decision Processes, Volume 62, p129-158.
• Leonard-Barton, D. (1995). Wellsprings of Knowledge. Boston, MA: Harvard Business School Press.
• Nonaka, I. and Takeuchi, H. (1995). The Knowledge-Creating Company. New York: Oxford University Press.
• Wielinga, B., Sandberg, J. and Schreiber, G. (1997). Methods and Techniques for Knowledge Management: What has Knowledge Engineering to Offer? Expert Systems with Applications, Vol. 13(1), p73-84.

Links

Projects and Participants

• Geodise
• myGrid
• Epistemics
• Southampton Intelligence, Agents, Multimedia group
• Manchester Information Management Group

Building Ontologies

• Alan Rector's paper on Untangling Taxonomies and Relationships, although not based on DAML+OIL and concentrating on medical ontologies, does however explore some of the issues and design decisions in large description logic ontologies
• More specific to DAML+OIL is Alan Rector's paper on the Normalisation of Ontologies
• Stanford's guide to Ontology Development, is geared towards Protege and frame based ontologies
• Asunción Gómez-Pérez has a large collection of presentations overviewing ontology methodologies and engineering
• February's Commuications of the ACM is a special issue on Ontologies. Visit the ACM and check on their Digital Library link

CommonKADS

• CommonKADS homepage

The Semantic Web and DAML+OIL

Most of this is for reference and other links only.

• A brief introduction to the semantic web and Oil, with some useful links as jump off points

• The Semantic Web site

• Download OilEd together with a brief manual and some examples from here

• If you are interested in the formal languages and their definitions, you can get full details of the DAML+Oil and Oil from:

  • Oil homepage
  • DAML homepage
  • DAML+Oil walk through
  • DAML+Oil technical reference

Example Project: Sisyphus III

In order to provide a concrete demonstration of the application of the CommonKADS approach to a realistic problem-opportunity area in knowledge engineering we present the results of work undertaken with respect to the Sisyphus III initiative.

During the Apollo moon program it came to be recognized that many of the primary scientific objectives of the missions could not be achieved without the astronauts acquiring a certain level of geological competence. This included the ability to undertake the collection and documentation of rock samples from the lunar surface. All of the moonwalkers except one - Harrison Schmidt - were taught their geology in snatched excursions with field geologists to selected sites in the USA, and via a limited number of class based lectures.

We can expect that future missions manned missions to the moon and other planets will also contain non-specialists who will be expected to carry out similar tasks. Sisyphus III represents an attempt to build a geological expert system for rock sample characterization.

The primary aim and value of the current demonstration material is to illustrate how the knowledge modeling tools and formalisms available within the CommonKADS framework can provide an effective specification of the knowledge and reasoning requirements of a prospective system within a circumscribed problem domain.

• Sisyphus III Website
• Sisyphus Knowledge Web (forthcoming)
• Sisyphus CML (forthcoming)
• Sisyphus XML (forthcoming)

Author: Paul Smart 
Last Updated: Monday, 11 November 2002