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Sharing.Knowledge.in.Collaborative.Moderation

Dalam dokumen Knowledge and Technology Management in (Halaman 147-152)

The use of moderators to support collaboration in virtual enterprises offers the opportunity for relevant knowledge held by individual partners to be shared in moderating the behaviour of the VE. However, issues of security and value of knowledge and experience which an individual partner may feel contributes to its competitive advantage also arise. In the VE environment, an individual company may be a partner in several distinct VEs at any one time.

While collaborating with a partner in one VE, each company may also be collaborating in other VEs which are in direct competition with one another: Indeed, the same company may be a partner in two directly-competing VEs. In this configuration, there is clear advantage to all partners in the network of VEs if a moderator specific to each VE can be populated not only with its own knowledge of how it operates, but with access to relevant subsets of each Figure 18. Moderation in VE ramp-up, operation and run-down

partners’ moderator knowledge base, the content of the accessible subset being strictly and clearly controlled by the partner so as to protect confidentiality and competitive advantage.

There is also the opportunity for each partner to access VE moderator knowledge and add to its own knowledge base for future use. This is illustrated in Figure 19.

Other.Future.Research.Areas

As highlighted at the start of this section, the quality of support that a moderator can provide is limited by the quality of knowledge gained through its KAM. To date, all knowledge acquired for the moderators has been provided by human experts. However, huge quantities of experience and expertise lie within the databases of manufacturing operations; hence an important future research area is:

• Knowledge discovery for moderation

The following are unconnected with manufacturing, but still considered to have potential moderator applications and therefore should be examined as future research areas:

• Scheduling applications (e.g., air traffic control, railway timetabling [planning and operations])

• Agent moderation in autonomous agent-based systems

• Pharmacology (e.g., identifying conflicts in medication) Figure 19. Shared access moderator knowledge

Conclusion

This chapter has provided an examination of how moderators, which are specialist intel- ligent software systems, contribute to Business Integration. It has provided a historical journey through changing and increasingly demanding and complex business requirements and business integration requirements, and has demonstrated how the initial single product, single enterprise-based Moderator concept has developed and exploited the increasingly powerful technologies and infrastructures available for business integration. Significant progress has been made since the early days of the first engineering moderator, but as shown in the “Where Next?”section, the challenges to be addressed in the future could be even more interesting.

References

Dhamankar, R., Lee, Y., Doan, A., Halevy, A., & Domingos, P. (2004). iMAP: Discovering complex semantic matches between database schemas. In Proceedings of the ACM SIGMOD International Conference on Management of Data ( SIGMOD 2004)(pp.

383-394), Paris, France.

Doan, A., Madhavan, J., Domingos, P., & Halevy, A. (2004). Ontology matching: A ma- chine learning approach. In S. Staab & R. Studer (Eds.), Handbook on ontologies (International Handbooks on Information Systems) (pp. 397-416). Berlin; Heidelberg:

Springer-Verlag/GmbH & Co.

Ehrig, M., Sure, Y., & Staab, S. (2005). Supervised learning of an ontology alignment pro- cess. In Proceedings of the 3rd Conference on Professional Knowledge Management, Workshop on IT Tools for Knowledge Management Systems: Applicability, Usability, and Benefits (IKMTOOLS 2005)(pp. 487-492), Kaiserslautern, Germany.

Fensel, D. (Ed.). (2002). Intelligent information integration in B2B electronic commerce.

Kluwer Academic Publishers.

Fensel, D., Ding, Y., Omelayenko, B., Schulten, E., Botquin, G., Brown, M., & Flett, A.

(2001). Product data integration in B2B e-commerce. IEEE Intelligent Systems, 16(4), 54-59.

Gruber, T. R. (1992). Toward principles for the design of ontologies used for knowledge sharing (Tech. Rep. No. KSL 93-04). Knowledge System Laboratory, Stanford Uni- versity.

Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, Elsevier Science, 5(2), 199-220.

Harding, J. A. (1996). A knowledge representation model to support concurrent engineering team working. PhD thesis, Loughborough University, UK.

Harding, J. A., & Popplewell, K. (1996). Driving concurrency in a distributed concurrent engineering project team: A specification for an engineering moderator. International Journal of Production Research, 34(3), 841-861.

Harding, J. A., & Yu, B. (1999). Information-centred enterprise design supported by a factory data model and data warehousing. Computers in Industry, 40, 23-36.

Hu, Z., Kruse, E., & Draws, L. (2003). Intelligent binding in the engineering of automation systems using ontology and Web services. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 33(3), 403 - 412.

Hyvönen, E., Saarela, S., & K. Viljanen, K. (2004). Application of ontology techniques to view-based semantic search and browsing. In Proceedings of the First European Semantic Web Symposium (ESWS 2004)(pp. 92-106), Heraklion, Crete, Greece.

Kosanke, K., Roland, J., & Nell, J. G. (Ed.). (2003). Enterprise inter- and intra-organi- zational integration: Building international consensus (International Federation for Information Processing).In Proceedings of the International Conference on Enter- prise Integration and Modeling Technology (ICEIMT’02),Valencia, Spain. Kluwer Academic Publishers.

Krause, F. L., Kimura, F., Kjellberg, T., & Lu, S. C. Y. (1993). Product modelling. Annals of the CIRP, 42(2), 695-706.

Lin, H. K. (2004). Manufacturing system engineering ontology model for global extended projects team. PhD thesis, Wolfson School of Mechanical and Manufacturing Engi- neering, Loughborough University, UK.

McKay, A., Bloor, M. S., & de Pennington, A. (1996, October). A framework for product data. IEE Transactions on Knowledge and Data Engineering, 8(5), 825-838.

McBride, B. (2002). Jena: A semantic Web toolkit. IEEE Internet Computing, 6(6), 55- 59.

Mena, E., & Illarramendi, A. (2001). Ontology-based query processing for global informa- tion systems. Kluwer Academic Publishers.

Molina, A., & Bell, R. (1999). A manufacturing model representation of a flexible manu- facturing facility. In Proceedings of the Institution of Mechanical Engineers: Part B, 213(3)(pp. 225-246).

Onosato, M., & Iwata, K. (1993). Development of a virtual manufacturing system by integrating product models and factory models. Annuals of the CIRP, 42(1), 475-478

Prahalad, C. K., & Hamel, G. (1990, May/June). The core competence of the corporation.

Harvard Business Review, 68(3), 79-91.

Priebe, T., & Pernul, G. (2003). Ontology-based integration of OLAP and information re- trieval. In Proceedings of the 14th International Conference on Database and Expert Systems Applications (DEXA 2003), Workshop on Web Semantics, (pp. 610-614) Prague, Czech Republic.

Stuckenschmidt, H., & van Harmelen, F. (2004). Information sharing on the semantic Web.

Berlin; Heidelberg: Springer-Verlag/GmbH & Co. K.

Endnotes

1 MOSES: Model-Oriented Simultaneous Engineering Systems—EPSRC Project Number (GR/H24273), 1992-1995.

2 Modelling and Simulation Environments for Design, Planning, and Operation of Globally-Distributed Enterprises (IMS/ESPRIT 29656) 1998 - 2001.

Chapter.VI

Dalam dokumen Knowledge and Technology Management in (Halaman 147-152)