The Noetic Prism

Definitions of ‘knowledge’ and its relationships with ‘data’ and ‘information’ are varied, inconsistent and often contradictory. In particular the traditional hierarchy of data-information-knowledge and its various revisions do not stand up to close scrutiny. We suggest that the problem lies in a flawed analysis that sees data, information and knowledge as separable concepts that are transformed into one another through processing. We propose instead that we can describe collectively all of the materials of computation as ‘noetica’, and that the terms data, information and knowledge can be reconceptualised as late-binding, purpose-determined aspects of the same body of material. Changes in complexity of noetica occur due to value-adding through the imposition of three different principles: increase in aggregation (granularity), increase in set relatedness (shape), and increase in contextualisation through the formation of networks (scope). We present a new model in which granularity, shape and scope are seen as the three vertices of a triangular prism, and show that all value-adding through computation can be seen as movement within the prism space. We show how the conceptual framework of the noetic prism provides a new and comprehensive analysis of the foundations of computing and information systems, and how it can provide a fresh analysis of many of the common problems in the management of intellectual resources.

[1]  Nagib Callaos,et al.  Toward a Systemic Notion of Information: Practical Consequences , 2002, Informing Sci. Int. J. an Emerg. Transdiscipl..

[2]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[3]  Vannevar Bush,et al.  As we may think , 1945, INTR.

[4]  Karl-Erik Sveiby The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets , 1997 .

[5]  M. Polanyi Chapter 7 – The Tacit Dimension , 1997 .

[6]  Dennis Nicholson The Intellectual Foundation of Information Organization , 2003 .

[7]  Ilkka Tuomi,et al.  Data is more than knowledge: implications of the reversed knowledge hierarchy for knowledge management and organizational memory , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[8]  Yogesh Malhotra,et al.  Knowledge Assets in the Global Economy: Assessment of National Intellectual Capital , 2000, J. Glob. Inf. Manag..

[9]  John Lionel Jolley The fabric of knowledge;: A study of the relations between ideas , 1973 .

[10]  Frank Miller,et al.  I=0 (information has no intrinsic meaning) , 2002, Inf. Res..

[11]  Thomas H. Davenport,et al.  Book review:Working knowledge: How organizations manage what they know. Thomas H. Davenport and Laurence Prusak. Harvard Business School Press, 1998. $29.95US. ISBN 0‐87584‐655‐6 , 1998 .

[12]  Yogesh Malhotra,et al.  Knowledge Management for E-Business Performance: Advancing Information Strategy to “Internet Time” , 2000 .

[13]  Theodore Roszak,et al.  The Folklore of Computers and the True Art of Thinking , 1986 .

[14]  Yoneji Masuda The information society as post-industrial society , 1980 .

[15]  H. Simon The Sciences of the Artificial, (Third edition) , 1997 .

[16]  Kent Sandoe Organizational mnemonics: exploring the role of information technology in collective remembering and forgetting , 1998 .

[17]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[18]  Stéphane Bressan,et al.  Introduction to Database Systems , 2005 .

[19]  Dorothy E. Leidner,et al.  Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues , 2001, MIS Q..

[20]  Luciano Floridi,et al.  Is Information Meaningful Data , 2005 .

[21]  Ralph Stair,et al.  Fundamentals of Information Systems , 2001 .

[22]  Umberto Eco,et al.  Semiotics and the philosophy of language , 1985, Advances in semiotics.

[23]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[24]  Ilkka Tuomi Data is more than knowledge: implications of the reversed knowledge hierarchy for knowledge management and organizational memory , 1999 .

[25]  M. J. Earl,et al.  Knowledge as strategy: reflections on Skandia International and Shorko Films , 1994 .

[26]  Jean E. Sammet,et al.  Programming languages - history and fundamentals , 1969, Prentice-Hall series in automatic computation.

[27]  Calvin N. Moore,et al.  Mooers' Law or Why Some Retrieval Systems Are Used and Others Are Not , 2005 .

[28]  Peter Checkland,et al.  Soft Systems Methodology in Action , 1990 .

[29]  G. Orange,et al.  The Three K's A model for knowledge that supports ontology and epistemology , 2002 .

[30]  S. Debowski Knowledge Management , 2005 .

[31]  Allen Newell,et al.  The Knowledge Level , 1989, Artif. Intell..

[32]  Rama Devi Tella Knowledge Management - Emerging Perspectives : A New Challenge for the Library Profession in the Digital Environment , 2007 .

[33]  Timothy R. Colburn Philosophy and Computer Science , 1999 .

[34]  E. F. CODD,et al.  A relational model of data for large shared data banks , 1970, CACM.

[35]  N. Bontis Assessing knowledge assets: a review of the models used to measure intellectual capital , 2001 .