DSS AND GIS IN KNOWLEDGE TRANSFORMATION PROCESS
Keywords:Tacit and explicit knowledge, SECI model, Operations Research and Management Science Models, Decision Support Systems, Geographical Information Systems, Models
Knowledge is an important resource for successful decision-making process in the whole society today. The special procedures of control and management of knowledge therefore have to be used. In the area of knowledge management and knowledge engineering basic terms of these disciplines are data, information, knowledge and knowledge transformation. The knowledge can be defined as a dynamic human process of justifying personal beliefs. Knowledge is a product of successful decision-making process. Knowledge transformation is a spiralling process of interactions between explicit and tacit knowledge that leads to the new knowledge. Nonaka and all show, that the combination of these two categories makes possible to conceptualise four conversion steps: Socialisation, Externalisation, Combination and Internalisation (SECI model). Another model of knowledge creation is the Knowledge Transformation Continuum (BCI Knowledge Group) that begins with the articulation of a specific instruction representing the best way that a specific task, or series of tasks, should be performed. Knowledge modelling and knowledge representation is an important field of research also in Computer Science and Artificial Intelligence. The definition of knowledge in Artificial Intelligence is a noticeable different, because Artificial Intelligence is typically dealing with formalized knowledge (e.g. ontology). The development of knowledge-based systems was seen as a process of transferring human knowledge to an implemented knowledge base. Decision Support Systems (DSS), Geographical Information Systems (GIS) and Operations Research/Management Science (OR/MS) modelling process support decision-making process, therefore they also produce a new knowledge. A Decision Support Systems are an interactive computer-based systems helping decision makers complete decision process. Geographic Information Systems provide essential marketing and customer intelligence solutions that lead to better business decisions. Operational Research and Management Science (OR/MS) is methodology based on system theory and theory of modelling. The OR/MS models serve for better quantification and precision of decision-making process. In this contribution the role of DSS, GIS and OR/MS models in the process of knowledge creation will be explained. The tacit or explicit character of this knowledge and the process of its creation will be explained and discussed.
Aamodt, A. and Nygard, M. (1995) ‘Different roles and mutual dependencies of data, information and knowledge’, Data & Knowledge Engineering, vol. 16, pp. 191-222.
Abecker, A., Decker, S., Hinkelmann, K., and Reimer, U. (1997) Workshop on Knowledge-Based Systems for Knowledge Management in Enterprises, Freiburg, Germany, Document D-97-03, DFKI GmbH.
Bernbom, G., (2001) ‘Information Alchemy: The Art and Science of Knowledge Management’, EDUCAUSE Leadership Series #3. San Francisco: Jossey-Bass. Graham, Ricci.
Brožová, H. and Šubrt, T. (2006) ‘Knowledge Creation in OR/MS Modelling Process’, Sci. Agri. Boh. Vol. 37, pp. 16 – 23.
Bullinger, H.-J., Wörner, K., and Prieto, J. (1997) Wissensmanagement heute. Fraunhofer Institut für Arbeitswirtschaft und Organisation, Stuttgart.
Davenport, T. H. (1996) Some Principles of Knowledge Management [online], Graduate School of Business, University of Texas at Austin, Strategy and Business, Available: http://www.bus.utexas.edu/kman.
Davenport, T. H. and Prusak, L. (1988) Working Knowledge. How Organizations manage what they know. McGraw-Hill; Harvard Business School Press.
Decker, S., Erdmann, M., Fensel, D. and Studer, R. (1999) ‘Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information’, In: R. Meersman et al. (Eds.), DS-8 Semantic Issues in Multimedia Systems, Kluwer Academic Publisher.
Decker, S. (2002) Semantic web methods for knowledge management.
Dretske, F. I. (1981) Knowledge and the flow of information. Basil Blackwell Publisher.
Erdmann, M. (2001) Ontologien zur konzeptuellen Modellierung der Semantik von XML. Dissertation, Institut AIFB, University of Karlsruhe.
Erdmann, M., Studer, R. (2001) ‘How to Structure and Access XML Documents With Ontologies’, In: Data and Knowledge Engineering, Special Issue on Intelligent Information Integration.
Fensel, D., Decker, S., Erdmann, M., and Studer, R. (1998a) ‘Ontobroker: Transforming the WWW into a Knowledge Base’, In Proceedings of the 11th Workshop on Knowledge Acquisition Modeling and Management, Banff, Canada, pp. 18-23.
Fensel D., Angele J., and Studer R. (1998b) ‘The Knowledge Acquisition and Representation Language KARL’, IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 4, pp. 527-550.
Fensel, D. (2000) ‘Problem-Solving Methods’, Lecture Notes in Computer Science (LNAI). Vol. 1791, Springer Verlag.
Heflin, J. (2001) Towards the Semantic Web: Knowledge Representation in a Dynamic, Distributed Environment. Ph.D. Thesis, University of Mary land, College Park.
van Heijst, G., Schreiber A. T., and Wielinga B. J. (1997) ‘Using Explicit Ontologies in Knowledge-Based System Development’, International Journal of Human-Computer Studies (IJHCS), vol. 46, no. 6.
van Heijst, G., van der Spek, R. and Kruizinga, E. (1998) The Lessons Learned Cycle. In: [Borghoff & Pareschi].
Klimešová, D. and Brožová, H. (2006) ‘Knowledge Management and Communication’, Proceedings of WMSCI 2006 - KCC 2006, Orlando, Florida, USA.
Klimešová, D. and Vostrovský, V. (2008) ‘Horizontal Integration of Knowledge’, Proceedings of the Twelfth IASTED International Conference, Artificial Intelligence and Soft Computing (ASC 2008), Palma de Mallorca, Spain.
Labrou, Y., Finin T. W. (1999) ‘Yahoo! As an Ontology: Using Yahoo! Categories to Describe Documents’, In: Proceedings of the 1999 ACM CIKM International Conference on Information and Know ledge Management, pp. 180-187, Kansas City, Missouri. November. ACM Press.
Leibold, M., Probst, G. and Gibbert, M. (2001) Strategic Management in the Knowledge Economy, Wiley, Erlangen.
O'Leary, D. (1998a) ‘Knowledge Management Systems: Converting and Connecting’, IEEE Intelligent Systems, May/June 1998, pp. 30-33.
O'Leary, D. (1998b) ‘Using AI in Knowledge Management: Knowledge Bases and Ontologies’, IEEE Intelligent Systems, May/June1998, pp. 34-39.
Machlup, F. and Mansfield, U. (Eds.) (1983) The study of information: Interdisciplinary messages (pp. 3–59). New York: John Wiley.
McCarthy, J. (1989) ‘Artificial Intelligence, Logic and Formalizing Common Sense’, In: R. Thomason (Ed.), Philosophical Logic and Artificial Intelligence, Dordrecht, Kluwer Academic.
Mitra, P., Kersten, M. and Wiederhold, G. (2000) ‘Graph-Oriented Model for Articulation of Ontology Interdependencies’, In: Proceedings of the 7th International Conference on Extending Database Technology, (EDBT).
Musen, M.A. (1993) ‘An Overview of Knowledge Acquisition’, In: David, J.M. et al. (Eds.), Second Generation Expert Systems, Springer-Verlag.
Nichols D. M. and Twidale M. B. (1999) ‘Computer supported cooperative work and libraries’, Vine, vol. 109, pp. 10-15 (special issue on Virtual communities and information services).
Nonaka, I. and Takeuchi, H. (1995) The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.
Nonaka, I, Konno, N. (1998) ‘The concept of "Ba’: Building foundation for Knowledge Creation’, California Management Review, Vol. 40, No.3, pp. 40-54.
Nonaka, I., von Krogh, G. and Ichijo,K. (2000) New Tools for Unlocking the Mysteries of Tacit Understanding, Oxford University Press.
Power, D., J. (2002) Decision Support Systems: Concepts and Resources for Managers, Quorum Books.
Probst, G., Raub, S. and Romhardt K. (1999) Managing Knowledge, London: Wiley.
Ribiere, M. and Matta, N. (1998) Virtual Enterprise and Corporate Memory. In: Abecker et al..
Staab, S., and Schnurr, H. P. (2000) ‘Smart Task Support through Proactive Access to Organizational Memory’, In: Journal of Knowledge-based Systems. Elsevier.
Studer R., Fensel D., Decker S., and Benjamins V. R. (1999) ‘Knowledge Engineering: Survey and Future Directions’, In: F. Puppe, (ed.), Knowledge-based Systems: Survey and Future Directions, Proceedings of the. 5th German Conference on Knowledge-based Systems, Würzburg, Lecture Notes in AI, Springer Verlag.
Studer, R., Decker, S., Fense, D. and Staab, S. (2000) ‘Situation and Prospective of Knowledge Engineering’, In: Cuena, J., Demazeau, Y., Garcia, A., Treur, J. (Eds.) Knowledge Engineering and Agent Technology. IOS Series on Frontiers in Artificial Intelligence and Applications. IOS Press.
Šubrt, T. and Brožová, H. (2007) ‘Knowledge Maps and Mathematical Modelling’, The Electronic Journal of Knowledge Management, Vol. 5, No. 4, pp. 497 - 504.
Sure, Y., Mädche, A., and Staab, S. (2000) ‘Leveraging Corporate Skill Knowledge - From ProPer to OntoProper’, In: Mahling, D., Reimer, U. (Eds.), Proceedings of the Third International Conference on Practical Aspects of Knowledge Management (PAKM 2000), Basel, Switzerland.
Sveiby, K. E. and Lloyd, T. (1990) Das Management des Know-how, Frankfurt am Main: Campus Verlag.
Tiwan, A (2002) The Knowledge Management Toolkit, Prentice Hall, New York.
http://www.bciknowledgegroup.com/knowledgeTransCycle.html: BCI Knowledge Group: Knowledge Transformation Cycle.
How to Cite
Authors declare with this manuscript intended for publication to ERIES Journal that:
- all co-authors agree with the publication of the manuscript even after amendments arising from peer review;
- all co-authors agree with the posting of the full text of this work on the web page of ERIES Journal and to the inclusion of references in databases accessible on the internet;
- no results of other researchers were used in the submitted manuscript without their consent, proper citation, or acknowledgement of their cooperation or material provided;
- the results (or any part of them) used in the manuscript have not been sent for publication to any other journal nor have they already been published (or if so, that the relevant works are cited in this manuscript);
- submission of the manuscript for publication was completed in accordance with the publishing regulations pertaining to place of work;
- experiments performed comply with current laws and written consent of the Scientific Ethics Committee / National Animal Care Authority (as is mentioned in the manuscript submitted);
- grant holders confirm that they have been informed of the submitted manuscript and they agree to its publication.
Authors retain copyright and grant ERIES Journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the published work with an acknowledgement of its initial publication in ERIES Journal. Moreover, authors are able to post the published work in an institutional repository with an acknowledgement of its initial publication in ERIES Journal. In addition, authors are permitted and encouraged to post the published work online (e.g. institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.