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A theory of information genetics: how four subforces generate information and the implications for total quality knowledge management - Statistical Data

Library Trends - January 1, 2002

ABSTRACT

THIS ESSAY PROPOSES A MODEL called information genetics (IG) to elaborate on the origin of information generating. The model builds on a broad information generating force that is both cause and effect. Part I of this essay postulates this information generating force as the result of the interaction and intermediation among four subforces: Query, command, statement, and term-term bond. These subforces are described by a process called twisting-bonding/clipping-jointing. The effect of this process is elaborated by: (1) Analyzing the Information Generating Model (IGM); (2) Transfiguring the Mobius Strip into the Mobius Twist Model; and (3) Demonstrating the process of the Clipping-Jointing Model. These three models are defined, exemplified, and described in detail. In Part II, a Fuzzy Commonality Model (FCM) is introduced to describe and explain the formation of a network curvature and to measure the dynamics of the twisting-bonding/clipping-jointing process within any special subject information field. In Part III, a software program is developed through the FCM for citation data mining, infomapping, and information repackaging--the three key elements in total quality knowledge management (TQKM). The conceptual and data models are supported by practical examples and statistical data. Several information flows are displayed in parallel to show their twisting-bonding/clipping-jointing interaction and intermediation relationships. This paper discusses the significance and advantages of the information genetics models and their approachability and applicability for TQKM in infomapping and Web information representation. The meaning of the information genetics models is also examined from a global perspective.

PART I: THEORY OF INFORMATION GENETICS

Introduction

There is a profound question constantly reappearing in teaching and researching in information storage and retrieval.

"What is it that makes the `UNIVERSAL' information generating, representation, and transfer happen?"

This question frequently recurs because any question-answering, problem-solving, and memory-recalling process (i.e., the process of incoming and outgoing thought itself, not the answer, problem, or memory) seems to be an enduring and endless task no matter how well, thoughtful, or diligent we conduct our information research activities.

To analyze this general question, it is necessary to break it into several subquestions:

1. What is the hidden driving force that causes information generating to occur?

2. Why does information generating occur?

3. How does information generating occur?

4. How can the information generating process in a subject field be efficiently and effectively monitored and measured?

5. How can an information generating force be harnessed for serving constructive purposes in any type of information business venture and endeavor?

The overall goal is to find out what the information generating force really is. Is there any hidden driving force that motivates and moves all types of information and thought processes and directs subsequent information representation and transferring conduct?

From computerized information processing, online and Internet searching, and Web-page design experiences, one has already learned that it is mainly a human interaction with a computer system that enables the information generating, representation, and transfer to happen. It is the computer's operating systems (i.e., control unit and arithmetic/logic unit) and its memory device (i.e., storage unit) in the CPU (central processing unit) that allow people to create, store, and retrieve files (see Figure 1). Therefore, a human endeavor properly interacting with a computerized information retrieval system and using proper communication protocol, logic, symbols, and operations, should successfully generate, represent, transfer, and flow information smoothly from place to place most of the time. Many times, people need a few trials to improve the quality of retrieved information and eliminate insufficiency, irrelevancy, inconsistency, uncertainty, pitfall, and inequity. However, in doing so, they can manage the work and get the job done eventually. So why should the above questions be so difficult to answer?

[FIGURE 1 OMITTED]

They are not so easy to answer because this "universal" information generating, representation, and transfer is not merely related to human or computerized information processing. It includes all forms and types of information processing in the "universe," both physical and cognitive. This "universality" of information processing, or the "phenomenon" involving the notion of information, has interested many researchers. An underlying question is: What is "information?" The next section reviews some leading definitions of "information."

Definition of Information Revisited

Jesse Shera (1970) considered information to be "a unit of thought," an "intellectual entity," and "the building block of knowledge." Brookes (1980) thought of information as an "entity which pervades all human activity," and suggested that "navigation maps" be used. Goffman (1970) pointed out that information science needs to establish "a set of fundamental principles governing the behavior of all communication processes and their associated information systems," regardless of the information phenomena that "are found in biological processes, in human existence, or in machines created by human beings" (p. 591). This point was supported by Pao (1989), who postulated that "information forms the foundation of all human existence" (p. 3). Devlin (1991) regarded information as "a basic property of the universe, alongside matter and energy (and being ultimately interconvertible with them)" (p. 2). He used a new term, infon, in parallel with electron, proton, neutron, photon, etc., and considered it as a semantic object, not a syntactic representation.

Many information researchers have also provided useful working definitions of "information." Shannon & Weaver (1949) viewed information as "a measure of the absence of uncertainty." Shannon & Weaver's application of entropy measurement stimulated chaos theorists to "redefine chaos as maximum information" (Hayles, 1989, p. 305). Conforming to Shannon & Weaver's -dew on information and entropy measurement, Goffman & Warren (1980) regarded information as "the amount of information once the uncertainty is removed" (p. 22). Hicks & Essinger (1991) valued the reduction or closure of "cognitive load," which they considered as "the burden being placed on the brain at any one time," and "the cause of stress, fatigue and making mistakes" (p. 58). Similarly, Breuning (1990) believed that "information overload is an inevitable part of our democracy" and cautioned that "cognitive pitfall is thus an inevitable part of public choice" (p. 219).

On the other hand, Machlup (1983) considered information as "a process," and knowledge "a state." To Soergel (1985), information is simply "data useful for decision making." Harmon viewed information, in terms of information measurement, as "energy that regulates other forms of energy" (Boyce & Kraft, 1985, p. 153), which can be viewed as a "meta-energy" in today's language. Debons, Horne,& Cronenweth (1988) illustrated the nature of information in terms such as commodity, energy, communication, facts, data, and knowledge. Kim (1990) supported Rathsworth's view on information, also defining it as a commodity, a process, a state of knowing, and an environment (from the system's notions). Zeleznikar (1990) regarded hermeneutics as "the study of informational occurrence or informing, the interpretation of informing within informational cycles" (p. 5). Meadow (1992) considered information as "something that (1) is represented by a set of symbols, (2) has some structure, and (3) can be read and to some extent understood by users of information" (p. 1). Tague-Sutcliffe (1995) summarized the definition of information as "what the user understands from the record during the time user and records are in contact" (p. 12).

The above authors basically elaborated upon and interpreted what information may be, how it is processed, and how the use of information is measured. Although their definitions are helpful in understanding the nature of information, they do not address the phenomenon of information generating.

This author, therefore, suggests a switch from the usual targets on information processing, information seeking, and information measurement to the phenomenon of information generating. This entails study of information twisting-bonding/clipping-jointing, particularly at the beginning moment of information generating, namely, the early stage of information processing.

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