The Theory of Infoledge: A Logical, Mathematical, and Geometrical Interpretation

By Alkhaldi, Firas M.; Olaimat, Mohammad M. | Issues in Informing Science & Information Technology, Annual 2008 | Go to article overview
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The Theory of Infoledge: A Logical, Mathematical, and Geometrical Interpretation


Alkhaldi, Firas M., Olaimat, Mohammad M., Issues in Informing Science & Information Technology


Introduction

Knowledge transfer questions: how, what and who energize the interest of researchers to revise the road map from information to knowledge, where the goals and interests definitely differ. According to Boisot and Griffith (2001) defined information as the meaning that is related to an observer's prior expectation when it is extracted from incoming data, where knowledge is the individual interpretation of the meaning of information that modifies the individual beliefs that reside in him. Information viewed as a message is meant to shape up the individual that gets it, to make some difference in his prospect and insight and it only becomes knowledge when it conveys meaning for the receiver. Davenport and Prusak (1998, p. 5) define knowledge as a fluid mix of framed experience, contextual information, values and expert insight that provides a framework for evaluating and incorporating new experiences and information. Achterbergh and Vriens (2002) stated that to determine whether a signal is informative, an observer has to append meaning to it, e.g., to perceive and interpret it. Once perceived and interpreted the observer may evaluate whether the signal is informative. It is essential to identify the observer according to our current discussion; however, as a primary entrance to the observer it is crucial to have quick and brief look at autopoietic theory.

Autopoietic Theory

Autopoietic theory considers the dynamics of living systems. The process called 'Autopoiesis' lies at the heart of this theory tries to detain the invariant attributes of living systems. Under Autopoietic theory, features like knowledge and beliefs arise in the domain of the observer, where someone watching a system interacts with its environment in such a way as to prompt the use of such terms. According to Koskinena, Pihlantob, and Vanharantaa (2003) autopoietic epistemology provides a fundamentally different understanding of the input coming from outside an organization. Input is regarded not as knowledge but as data, i.e. knowledge is data put into a certain context. This means that knowledge cannot be directly conveyed as knowledge from one individual to another, because data have to be interpreted -see Figures 1 and 3. Also, it was declared by that knowledge is a component of the autopoietic, i.e. self-productive process. This means that knowledge context dependent and situation sensitive (Maturana & Varela, 1987; Varela, Thompson, & Rosch, 1991).

According to Vicari and Troilo (1999) the only way to acquire new knowledge is to utilize existing knowledge since knowledge cannot be transmitted but only produced.

The Observer

The nervous system recursively interrelate its components leading the organism to generate, maintain and re-engage its own states as if they were literal re-presentations of external phenomena. Such states are 'second-order' in the sense that they are derivative from experience. These states are called descriptions in autopoietic theory, and an organism operating within the realm of its descriptions is an observer. 'An observer is a ... living system who can make distinctions and specify that which he or she distinguishes as a unity, as an entity different from himself or herself that can be used for manipulations or descriptions in interactions with other observers.' (Maturana, 1978, p. 31). The observer is one of the key concepts in autopoietic theory, because: 'Observing is both the eventual starting point and the most basic question in any effort to comprehend reality and reason as phenomena of the human domain. Indeed, everything said is said by an observer to another observer that could be him- or herself (Maturana, 1988, p. 27).

Data-Wisdom Conversion Spectrum

Autopoietic systems are both closed and open. Open to data, but closed to information and knowledge, both of which have to be interpreted inside the system where input is regarded as data only.

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