I-Space

The Information Space, or I-Space was developed by Max Boisot as a conceptual framework relating the degree of structure of knowledge (i.e. its level of codification and abstraction) to its diffusibility as that knowledge develops.

This results in four different types of knowledge.^[1]

• Public knowledge, such as textbooks and newspapers, which is codified and diffused.
• Proprietary knowledge, such as patents and official secrets, which is codified but not diffused. Here barriers to diffusion have to be set up.
• Personal knowledge, such as biographical knowledge, which is neither codified nor diffused.
• Common sense – i.e. what ‘everybody knows’, which is not codified but widely diffused.

The I-Space model is commonly shown as a cube with three axes: abstraction, codification and diffusion. A social learning cycle is drawn, showing how as knowledge is increasingly moved from concrete experiential Zen type knowledge to codified highly abstract (expert language etc.), where it is increasingly easy for it to diffuse independently of the knowledge holder. Once internalised it moves back to the concrete.^[2]

The I-Space framework is an acknowledged early influence on the development of the Cynefin framework.^[3]

See also

• The SECI Model

References

1. Boxer, P, "Managing over the whole Governance Cycle", Asymmetric Design, April 2006
2. Snowden, D (2010) "The origins of Cynefin (part 1)" Cognitive Edge March 2010
3. Snowden, D. (2002) “Complex Acts of Knowing: Paradox and Descriptive Self Awareness” in the Journal of Knowledge Management – Vol. 6, No. 2 (May), pp. 100–111

Further reading

• Boisot, Max (1999). "The I-Space: a framework for analyzing the evolution of social computing". Technovation 19 (9): 525–536. ISSN 0166-4972. Retrieved 1 November 2011.
• Boisot, Max (May 2004). "Exploring the information space: a strategic perspective on information systems". IN3 Internet Interdisciplinary Institute. Retrieved 1 November 2011.
• Casillas-Santillan, Luis Alberto (August 2005). "A Multidimensional Model To Map Knowledge". Journal of Knowledge Management Practice. Retrieved 1 November 2011.
• Leong, Lam Chuan. "Complexity, Bureaucracy and the Information Space" (PDF). Ethos (Jul–Sep 2005). Retrieved 11 June 2010.
• Savory, Clive (2006). "Translating knowledge to build technological competence". Management Decision 44 (8): 1052–1075. doi:10.1108/00251740610690612. Retrieved 11 June 2010.