Abstract
The notion of knowledge is omnipresent in the field of knowledge management and knowledge organisation. This chapter begins with an epistemological reflection on the systems involved in the processes of representing, transferring and managing knowledge. It will be shown that knowledge is fundamentally tied to the process of cognition. By implication, knowledge has to be understood as a highly dynamic process emerging from the interaction between a cognitive system, its natural environment and its non-natural environment (for example artefacts, symbols and so on). Based on these epistemological insights, a framework will be developed to offer some orientation in the ‘jungle’ of notions and concepts of knowledge. The various dimensions of knowledge (such as local-distributed, representational-situated, mapping construction and so on) will be discussed, together with their relevance to the field of knowledge management. Investigation of the object of knowledge reveals that technological and information processing approaches to knowledge management and to our everyday knowledge cover only a small fraction of what knowledge actually comprises.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ashby, R. W. (1964) An Introduction to Cybernetics (London: Methuen).
Barlow, B. (1972) ‘Single units and sensation: a neuron doctrine for perceptual physiology’, Perception, vol. 1, no. 1, pp. 371–94.
Bechtel, W. and Abrahamsen, A. (2001) Connectionisrn and the Mind. Parallel Processing, Dynamics, and Evolution in Networks (Malden, Mass., and Oxford: Blackwell).
Bechtel, W. and Graham, G. (eds), (1998) A Companion to Cognitive Science (Oxford: Blackwell).
Bischof, N. (1998) Struktur und Bedeutung. Eine Einführung in die Systemtheorie für Psychologen (Bern: Hans Huber).
Brook, A. and Stainton, R. J. (2000) Knowledge and Mind. A Philosophical Introduction (Cambridge, Mass.: MIT Press).
Brooks, R. A. (1991) ‘Intelligence without representation’, Artificial Intelligence, vol. 47, pp. 139–59.
Bukowitz, W. R. and Williams, R. L. (1999) The Knowledge Management Fieldbook (London: Prentice-Hall).
Cangelosi, A. and Parisi, D. (eds) (2002) Simulating the Evolution of Language (Berlin and New York: Springer).
Churchland, P. M. (1979) Scientific Realism and the Plasticity of Mind (Cambridge and New York: Cambridge University Press).
Churchland, P. M. (1988) Matter and Consciousness. A Contemporary Introduction to the Philosophy of Mind (Cambridge, Mass.: MIT Press).
Clark, A. (1989) Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing (Cambridge, Mass.: MIT Press).
Clark, A. (1999) ‘An embodied cognitive science?’, Trends in Cognitive Sciences, vol. 3, no. 9, pp. 345–51.
Clark, A. (2001) Mindware. An Introduction to the Philosophy of Cognitive Science (New York: Oxford University Press).
Davenport, T. H. and Prusak, L. (1998) Working Knowledge. How Organizations Manage What They Know (Boston: Harvard Business School Press).
Dienes, Z. and Perner, J. (1999) ‘A theory of implicit and explicit knowledge’, Behavioral and Brain Sciences, vol. 22, no. 5, pp. 735–55.
Elman, J. L. (1991) ‘Distributed representation, simple recurrent networks, and grammatical structure’, Machine Learning, vol. 7, nos 2/3, pp. 195–225.
Fodor, J. A. and Pylyshin, Z. W. (1998) ‘Connectionism and cognitive architecture: a critical analysis’, Cognition, vol. 28, pp. 3–71.
Gelder, T. J. v. (1992) ‘Defining “distributed representation”’, Connection Science, vol. 4, nos 3/4, pp. 75–191.
Gelder, T. J. v. (1998) ‘The dynamical hypothesis in cognitive science’, Behavioral and Brain Sciences, vol. 21, pp. 1–14.
Harman, G. (1998) ‘Intentionality’, in W. Bechtel and G. Graham (eds), A Companion to Cognitive Science (Oxford: Blackwell).
Hamad, S. (1990) ‘The symbol grounding problem’, Physica, vol. 42, pp. 335–46.
Hinton, G. E., McClelland J. L. and Rumelhart D. E. (1986) ‘Distributed representations’, in D. E. Rumelhart and J. L. McClelland (eds), Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundations (Cambridge, Mass.: MIT Press), pp. 77–109.
Hoffmann, A. G. (1998) Paradigms of Artificial Intelligence: A Methodological and Computational Analysis (Berlin and New York: Springer).
Kornblith, H. (ed.) (1993) Naturalizing Epistemology (Cambridge, Mass.: MIT Press).
Kosslyn, S. M. (1990) ‘Mental imagery’, in D. N. Osherson and H. Lasnik (eds), An Invitation to Cognitive Science (Cambridge, Mass.: MIT Press), pp. 73–97.
Kosslyn, S. M. (1994) Image and Brain. The Resolution of the Imagery Debate (Cambridge, Mass.: MIT Press).
Liebowitz, J. (1999) Knowledge Management Handbook (London and New York: Routledge & Kegan Paul).
Martin, J. H. (1991) ‘Coding and processing of sensory information’, in E. R. Kandel, J. H. Schwartz and T. M. Jessel (eds), Principles of Neural Science (New York: Elsevier), pp. 329–40.
Maturana, H. R. and Varela, F. J. (eds) (1980) Autopoiesis and Cognition: The Realization of the Living (Dordrecht and Boston: Reidel).
McLeod, P. M., Plunkett, K. and Rolls, E. T. (1998) Introduction to Connectionist Modelling of Cognitive Processes (Oxford and New York: Oxford University Press).
Nilsson, N. J. (1998) Artificial Intelligence: A New Synthesis (San Mateo, CA: Morgan Kaufman).
Nonaka, I. and Takeuchi, H. (1995) The Knowledge Creating Company. How Japanese Companies Manage the Dynamics of Innovation (Oxford: Oxford University Press).
Oeser, E. (1976) Wissenschaft und Information: systematische Grundlagen einer Theorie der Wissenschaftsentwicklung (Vienna and Munich: Oldenburg).
Peschl, M. F. (1994) Reprasentation und Konstruktion. Kognitions- und neuroinformatische Konzepte als Grundlage einer naturalisierten Epistemologie und Wissenschaftstheorie (Braunschweig and Wiesbaden: Vieweg).
Peschl, M. F. (1997) ‘The Representational Relation Between Environmental Structures and Neural Systems: Autonomy and Environmental Dependency in Neural Knowledge Representation’, Nonlinear Dynamics, Psychology, and Life Sciences, vol. 1, no. 2, pp. 99–121.
Peschl, M. F. (1999) ‘The development of scientific theories and their embodiment in the representational activities of cognitive systems. Neural representation spaces, theory spaces and paradigmatic shifts’, in P. v. Loocke (ed.), The Nature of Concepts (London: Routledge & Kegan Paul), pp. 184–214.
Peschl, M. F. (2001) ‘Constructivisrn, cognition, and science. An investigation of its links and possible shortcomings’, Foundations of Science, vol. 6, no. 1, pp. 125–61.
Pfeifer, R. and Scheier, C. (1999) Understanding Intelligence (Cambridge, Mass.: MIT Press).
Polanyi, M. (1966) The Tacit Dimension (Garden City, NY: Doubleday).
Popper, K. R. (1934) The Logic of Scientific Discovery (New York: Basic Books).
Port, R. and. Gelder, T. J. v (eds) (1995) Mind as Motion: Explorations in the Dynamics of Cognition (Cambridge, Mass.: MIT Press).
Probst, G., Raub, S. and Romhardt, K. (1999) Wissen managen. Wie Unternehmen ihre wertvollste Ressource optimal nutzen (Frankfurt/M: Gabler).
Procter, R. W. (2002) ‘Knowledge elicitation methods and their major advantages and disadvantages. Communications of the ACM Tables’, http://www. psych.purdue.edu/proctor/ACM_tables.pdf.
Rasmussen, S. (1991) ‘Aspects of Information, Life, Reality, and Physics’, in C. G. Langton, C. Taylor, J. D. Farmer and S. Rasmussen (eds), Artificial Life II (Redwood City, CA: Addison-Wesley), pp. 767–73.
Roth, G. (1991) ‘Die Konstitution von Bedeutung im Gehirn’, in S. J. Schmidt (ed.), Geddchtnis. Probleme und Perspektiven der interdisziplinaren Gedachtnisforschung (Frankfurt/M: Suhrkamp), pp. 360–70.
Rumelhart, D. E., Hinton, G. E. and McClelland, J. L. (1986) ‘A general framework for parallel distributed processing’, in D. E. Rumelhart and J. L. McClelland (eds), Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundations (Cambridge, Mass.: MIT Press), pp. 45–76.
Rumelhart, D. E. and McClelland, J. L. (1986) ‘On learning the past tenses of English verbs’, in J. L. McClelland and D. E. Rumelhart (eds), Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Psychological and Biological Models (Cambridge, Mass.: MIT Press), pp. 216–71.
Schmidt, S. J. (ed.) (1987) Der Diskurs des Radikalen Konstrukrivismus (Frankfurt/M: Suhrkamp).
Schmidt, S. J. (ed.) (1992) Kognition und Gesellschaft. Der Diskurs des Radikalen Konstruktivismus2 (Frankfurt/M: Suhrkamp).
Shannon, C. E. (1949) The Mathematical Theory of Communication (Urbana, Ill.: University of Urbana Press).
Smolensky, P. (1988) ‘On the proper treatment of connectionism’, Behavioral and Brain Sciences, vol. 11, pp. 1–74.
Thelen, E. and Smith, L. B. (1994) A Dynamic Systems Approach to the Development of Cognition and Action (Cambridge, Mass.: MIT Press).
Turing, A. (1936) ‘On computable numbers, with an application to the entscheidungsproblem’, Proceedings of the London Mathematic Society, vol. 42, pp. 230–65.
Turing, A. (1950) ‘Computing machinery and intelligence’, Mind, vol. 59, no. 236, pp. 433–60.
Varela, F. J., Thompson, E. and Rosch, E. (1991) The Embodied Mind: Cognitive Science and Human Experience (Cambridge, Mass.: MIT Press).
von Foerster, H. (1973) ‘On constructing a reality’, in P. Watzlawick (ed.), The Invented Reality (New York: Norton), pp. 41–61.
von Glasersfeld, E. (1983) ‘On the concept of interpretation’, Poetics, vol. 12, no. 3, pp. 254–74.
von Glasersfeld, E. (1984) ‘An introduction to radical constructivism’, in P. Watzlawick (ed.), The Invented Reality (New York: Norton), pp. 17–40.
von Glasersfeld, E. (1991) ‘Knowing without metaphysics. Aspects of the radical constructivist position’, in F. Steier (ed.), Research and Reflexivity (London and Newbury Park, CA: Sage), pp. 12–29.
von Glasersfeld, E. (1995) Radical Constructivism: A Way of Knowing and Learning (London: Falmer).
Ward, L. M. (2002) Dynamical Cognitive Science (Cambridge, Mass.: MIT Press).
Wiener, N. (1948) Cybernetics: Control and Communication in the Animal and the Machine (New York: Wiley).
Wilson, R. A. and Keil, F. C. (eds) (1999) The MIT Encyclopedia of the Cognitive Sciences (Cambridge, Mass.: MIT Press).
Winograd, T. and Flores, F. (1986) Understanding Computers and Cognition: A New Foundation for Design (Norwood, NJ: Ablex).
Zeigler, B. P., Praehofer, H. and Kim, T. G. (2000) Theory of Modeling and Simulation. Integrating Discrete Event and Continuous Complex Dynamic Systems (San Diego, CA: Academic Press).
Editor information
Editors and Affiliations
Copyright information
© 2004 Markus Franz Peschl
About this chapter
Cite this chapter
Peschl, M.F. (2004). Structures and Diversity in Everyday Knowledge: From Reality to Cognition, Knowledge and Back. In: Gadner, J., Buber, R., Richards, L. (eds) Organising Knowledge. Palgrave Macmillan, London. https://doi.org/10.1057/9780230523111_1
Download citation
DOI: https://doi.org/10.1057/9780230523111_1
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-51290-4
Online ISBN: 978-0-230-52311-1
eBook Packages: Palgrave Business & Management CollectionBusiness and Management (R0)