Knowledge Management processes

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What is Knowledge Management?

Shift in understanding knowledge

Access to knowledge and the ability to use it wisely have always been the hallmark of successful individuals, companies, and even nations. Thus the recognition that knowledge has great value has been with us for a long time. But until fairly recently, most people did not think in terms of “managing knowledge”; they rather felt that knowledge was a personal asset as the sum of our experiences, education, and our informal community of friends and colleagues that can be trusted to help perform better in our complex world.

As computer technology improved and became cheaper in the early 1990’s, researchers in academia, government, and private industry began to explore the gains that could be made by organizing (Hjerland 2003)[1] knowledge, codifying it, and sharing (Neches et al. 1991)[2] it more widely. The early innovators began to demonstrate that actively improving the management of knowledge could help scientists improve getting their research results into the hands of users.

The idea of "augmenting human intelligence" appeared already as early as in 1960's (Engelbart 1962)[3]. Recent theoretical discourse about trialogical approach of learning (Paavola and Hakkarainen 2009)[4] views electronic resources as mediating tools, i.e. as a third essential component in contemporary knowledge management alongside individuals and the surrounding community.

Explicit and tacit knowledge

Knowledge exists in either explicit or tacit states. Explicit knowledge is knowledge that has been codified in some way such as scientific journal articles, operating procedures, databases, etc. Tacit knowledge in turn refers to the knowledge that people carry in their minds. It consists of subjective opinions, intuition, feelings or judgments. People often do not explicitly know about their own knowledge stores (“we know more than we know how to say”, Polyani 1958)[5].

Knowledge about natural resource management is multifaceted and spans a broad spectrum of spatial, temporal and process scales. Various forms and Types of knowledge can be found. Its domains are biological, physical and social (Simard 2000 [6], Innes 2003[7]). Declarative knowledge like facts, propositions or schemas provide general knowledge about the behavior and functioning of ecosystems. It includes episodic knowledge (specific time and place events) and semantic knowledge (facts and general information). Procedural knowledge is about how to do things. Individuals, companies, organizations, universities and nations provide a rich mixture of ideas, contextually relevant facts and expertise for declarative and procedural knowledge.

Definition of Knowledge Management (KM)

Knowledge management, then, can be defined as the systematic strategy of creating, conserving, and sharing knowledge to increase the performance of individuals, companies, or nations (Heinrichs et al. 2003) [8]. Knowledge management attempts to provide methods for managing both explicit and tacit knowledge. Sometimes this means primarily socially-based methods that help person-to-person knowledge exchanges. Other methods can take advantage of existing explicit knowledge that has already been codified for other purposes to make it more readily accessible (Hansen et al. 1999 [9]). But knowledge management also concentrates on methods that help the process of moving from tacit knowledge to explicit knowledge and thus expand the amount of codified knowledge available for use (Heinrichs et al. 2003). Nonaka and Takeuchi (1995)[10] describe a typology of knowledge practices based on the conversion of knowledge from one form to another:

  • Socialization: where tacit knowledge is shared through shared experiences by individuals;
  • Externalization: where tacit knowledge is articulated into explicit knowledge with the help of metaphors and analogies;
  • Combination: where explicit knowledge is systemized and refined e.g. by utilizing information and communication technologies and existing databases;
  • Internalization: where explicit knowledge is converted into tacit knowledge, e.g. by learning by doing.

Knowledge Management isn't contain IT, but IT offers better way to share information (Knowledge Management System, KMS).

Managing Knowledge in the Field of Natural Resources and Forest Management

The natural resource field has been the subject of several early attempts to demonstrate the value of applying KM principles focusing on explicit knowledge. Rauscher (1987)[11] introduced the concept of modern knowledge management to the natural resource field in the same year that the first hypertext software programs became available. As the Internet became more popular, it was obvious that knowledge management systems using web-based hypertext had an enormous competitive edge over stand-alone systems. Saarikko (1994)[12] reported on an early comprehensive summary of the forestry information resources on the Internet. Current comprehensive portal to such information is the Global Forest Information Service (GFIS), coordinated by IUFRO.

Examples of modern natural resource management KM systems on the Internet can be found at the Forest Encyclopedia Network Forest Encyclopedia Network where a growing number of scientific encyclopedias can be found (Kennard et al. 2005)[13].

Knowledge management tools do not manage knowledge by themselves but rather facilitate the implementation of knowledge processes. They promote and enable the knowledge process by identifying, creating, structuring and sharing of knowledge through the use of information technology in order to improve decision-making (Tyndale 2992)[14]. A preliminary table of KM tools that could be integrated in forest management DSS's is presented in the Workplan of FORSYS WG 3, and it is further developed on this neighbouring wiki page.

Different business units use different definition for the same meaning. And same definitions can be meant different concepts among different business units. Single version of truth is a technique, which provides meanings to be the same for all units. Embodiments herein, in this case (FORSYS), we should make sure that all participants think the same of every single concepts. To support a common understanding, the following working pages are relevant:

Classification of knowledge management techniques

In most cases various KM approaches (compare Description of knowledge management techniques) will be used to develop components of DSS and they will be partly integrated where information, data and conceptual knowledge is captured. The way how KM approaches, communication tools and methods in general are integrated in DSS will be described and categorized according to (i) their contribution to support decision makers in the decision making phases intelligence, design, choice, monitoring (ii) their importance for one of the knowledge management processes identification, generation, evaluation, storage, transfer and application.

To support a common understanding, the following working pages are relevant:


References

  1. Hjerland, B. (2003). Fundamentals of knowledge organization. Knowledge Organization, 30(2), 87-111.
  2. R. Neches, R. Fikes, T. Finin, T. Gruber, R. Patil, T. Senator, & W. R. Swartout. Enabling technology for knowledge sharing. AI Magazine, 12(3):16-36, 1991.
  3. Engelbart, D.C., Augmenting Human Intellect: A Conceptual Framework, Stanford Research Institute, AFOSR-3223, October 1962.
  4. Paavola, S. & Hakkarainen, K. (2009). From meaning making to joint construction of knowledge practices and artefacts – A trialogical approach to CSCL. In: C. O'Malley, D. Suthers, P. Reimann, & A. Dimitracopoulou (Eds.), Computer Supported Collaborative Learning Practices: CSCL2009 Conference Proceedings. (pp. 83-92). Rhodes, Creek: International Society of the Learning Sciences (ISLS) (draft available online).
  5. Polanyi, M. (1958) Personal Knowledge, Chicago
  6. Simard, A.J. (2000) Managing Knowledge at the Canadian Forest Service, Science Branch Canadian Forest Service, Ottawa, p.88.
  7. Innes, T. (editor). (2003) Natural Resources Information Management Forum: Putting knowledge to work. FORREX –Forest Research Extension Partnership, Kamloops, B.C.FORREX Series No.8.
  8. Heinrichs, J. H.; Hudspeth, L. J. and Lim, J. S. (2003) Knowledge management. In: Hossein Bidgoli, ed., Encyclopedia of Information Systems, Academic Press, Volume 3: 13-31.
  9. Hansen M. T.; Nohria, H. and Tiernex, T. (1999) What’s your strategy for managing knowledge? Harvard Business Review 77 (2)
  10. Nonaka I., and Takeuchi, H. (1995) The Knowledge-Creating Company, Oxford University Press, Inc.
  11. Rauscher, H. M. (1987) Increasing scientific productivity through better knowledge management. AI Applications 1(2): 21-31.
  12. Saarikko, J. (1994) Forestry information resources on the Internet (http://www.funet.fi/pub/sci/forest/doc/guides/Saarikko-1994b.html)
  13. Kennard, D. K.; Rauscher, H. M., Flebbe, P. A., Schmoldt, D. L., Hubbard, W. G., Jordin, J. B. and Milnor, W. (2005) Using hyperdocuments to manage scientific knowledge: the prototype Encyclopedia of Southern Appalachian Forest Ecosystems. Forest Ecology and Management 207: 201-213.
  14. Tyndale, P. (2002) A taxonomy of knowledge management software tools: origins and applications, Evaluation and Programm Planning 25: 183 – 190.