Written for IS580, 4/16/2005.
Using solely the quantitative, classical scientific method in information science is like trying to fit a square peg through a round hole. Trying to study information without considering the human factor involved is impractical. Trying to study information in a purely hard science fashion is impossible, because it is not an observable natural phenomenon but a social phenomenon. The products of the research will end up not the square peg you were striving for, but the round peg you shaped it to be. “Information is a social construct, and communication of information is a social event. Attempts to develop ‘proofs’ for arguments related to social phenomena are bound to fail… In any human problem-solving endeavor, there is inevitably an incompleteness of data that blocks any credible law or rule” (Neill 140). The domains of information science are social, not natural, and to force-fit a purely natural science approach prevents the researcher from fully exploring the subject. “The use of fuzzy set or possibility theory in an effort to put some numbers on uncertainty is too limited to handle the intricacies and scope of the social issue that is information retrieval and knowledge production” (Neill 141). Quantitative analysis alone is insufficient, but that is not to say it does not have its place within information science.
Information science can still benefit from the principles of the scientific method. The idea that it must use one type of methodology or the other, either qualitative or quantitative but not both, is misleading, These two methodologies are not mutually exclusive and in fact can complement each other in practice. The classical ethnographic tradition in sociocultural anthropology uses both methods without characterizing one as superior over the other. “By breaking down the artificial distinction between qualitative and quantitative research, scientific ethnography holds the promise of reconciling the intractable ‘two-cultures’ mentality that permeates social research” (Sandstrom 192). Scientific ethnography distinguishes between emic (insider’s view) and etic (outsider’s view) data while still valuing both. Sandstrom and Sandstrom argue that the ethnographic method is misconstrued and misused in LIS, and that many of the issues currently debated within LIS (observer effects, conflicting perspectives, etc) have already been addressed many times in sociocultural anthropology. They discuss several related concepts identifying the separate metaphors of the cognitive and the physical: “(1) the tension between science and nonscience; (2) the emic-etic distinction; (3) the unproductive perpetuation of a qualitative-quantitative dichotomy; (4) the interplay of inductive and deductive strategies” (Sandstrom 164). These opposing metaphors all serve their purpose in information science, and one need not be used to the exclusion of the other. Brookes states that because social scientists cannot be sure that the act of observation does not affect their subject as a natural scientist can, that “the boundary between objective and subjective becomes very fuzzy indeed” (Brookes 126). The line between the emic and the etic is hard to define in the social sciences, but if both methods are equally valued then pinning down the boundaries between them becomes less important.
The ethnographic method uses a variety of research techniques. It does not rely on one overriding paradigm. The bisection of methodology into science vs. nonscience, emic vs. etic, qualitative vs. quantitative, is not a core problem in anthropology as it is in information science. Sandstrom and Sandstrom assert that the qualitative approach does not necessarily mean an unscientific approach. A part of the underlying problem may be that the “nonscience” research methodology is viewed as somehow inferior to the “science” methodology, while anthropologists (possibly because their field is so focused on human beings themselves rather than the products of human thought) do not have such an inferiority complex over using the “nonscience” methodology, because in anthropological theory it is just as strong and valid an approach as the classical scientific method is to a biologist. Information scientists resist it. I would characterize it as the middle child, looking up to his older brother Hard Science and wanting to be superior to his younger brother Soft Science, while being neither one nor the other but pieces of both. The Sandstroms also make a good point that many of the writings of anthropologists are being duplicated by information scientists. Information scientists should “seek out the quality research, whatever its method or era” (Bates 1) rather than re-inventing the wheel and duplicating research that has already been done.
The concept of information within the field of information science is nebulous and ill-defined. It has so many definitions that in effect, it doesn’t have any definition. “The work of the information profession, by its nature, is responsible for the dilemma over which type of research is most valid for information science” (Neill 155). Is the uncertainty over definitions and terminology inextricably linked to the lack of clarity in the discipline? There is a lot of “mud” and confusion in information science, resulting from the lack of a concrete theoretical foundation which is basic to most hard sciences. Can one be cleared up without clearing up the other? When information is clearly defined and the extent of the field marked out, then will methodology necessarily follow in a hard science manner so that we really are a science and not a humanity or social science? Information is something of a two-edged sword when regarded by information science: at once physical and cognitive, a thing and a process, a part of all three of Karl Popper’s worlds, the material, mental, and noetic domains. It is neither one nor the other but both, just as information science is neither a hard nor soft science but both, depending on the aspect of information that is being studied.
The important aspect of information with regards to information science is its meaning. Information without meaning and knowledge is purposeless. Natural science principles (gravity, etc) would exist independently of humans. Even if we weren't there to measure them and test them, they would still be there, doing their thing and exerting their forces. Gravity works on the moon with no humans to interfere or interact with it. Information does not exist without a mind to interact with. Without human processing, information is just pieces of data, meaningless and without context or relevance. Animals may process data instinctually, but in a wholly different fashion than a human consciousness. The key is sentience, being aware of the information process and assigning meaning to it. Buckland asserts that “information has to do with becoming informed, with the reduction of ignorance and of uncertainty” (Buckland 351). All of this implies the integral role of a human being: the person who becomes informed, whose ignorance and uncertainty is reduced. It also implies that information must have meaning, as information without meaning cannot inform or reduce ignorance.
If one of the purposes of information science is to provide access to information, then meaning is inherently important. Providing access implies a human connection, the person to whom access is provided, and that the information will be meaningful or become meaningful to the person accessing it, and be processed into knowledge. “To complete the act of communication requires a twofold act of participation. First, a willful apprehension of information on the part of an individual must occur in order to access and use an informative object. Second, a cognitive transformation of that object must occur for it to enter into a meaningful and relevant relation to the problem that motivates and conditions participation” (Raber 250). Information as a theoretical concept is inherently linked to meaning and knowledge within the domain of information science because it is inherently linked to human beings.
Information, meaning, knowledge, and communication are inextricably linked within the domain of information science. Information necessarily carries meaning, and is transmitted via communication to a receptor where it becomes knowledge. Claude Shannon, though discussing mathematical communication theory, constructed a model for the process of communication that is equally applicable to human communication. The source person transmits or communicates a message (meaningful information) to a receiver person (Raber 67). The channel, or format of communication, can take many forms (art, text, music, etc.) but the process remains the same. The meaning of the information may be different to the source and receiver, but it is still information. Information, meaning, knowledge, and communication are the foundational concepts of information science. Information science must incorporate all of them because they are so closely related. Defining any one of these terms without mentioning some aspect or concept of the others would be difficult, and so all four are necessarily part of the foundations of information science. Pinning down an exact definition to concepts that seem intuitively easy to understand has been difficult, and in the end the concepts are regarded pragmatically in their usage within the discipline. “Whatever foundations [information science] may claim to have rest on commonsense views of language, of communication, of knowledge and information” (Brooks 125).
“By naming themselves information scientists the members of [the Institute of Information Scientists] obviously wanted to stress the importance of the study of (scientific) information and the processes involved in scientific communication. Hereby their work was a continuation of previous scientific attempts to deal with problems of organization, growth and dissemination of recorded knowledge” (Ingwersen 2). The name of the field is one of the primary concepts and also one of the most ambiguous. If, as Neill says, the work of information science is responsible for its dilemma of research methodology, is the name of information science responsible for its indeterminate boundaries? Information science is interdisciplinary in nature and frequently overlaps with and incorporates other fields or disciplines, such as computer science, logic, and linguistics. It is a young discipline and is still evolving but it has grown into its chosen name. Information science, like most disciplines, names itself for what it studies. Its core focus, nebulous though the concept may be, is information in its many aspects, and so the name information science is appropriate. As anthropologists study man (anthropos), information scientists could also be pliroforologists, but there’s enough incertitude in the discipline without adding an obscure Greek word into the mix.
Marianne Moore describes poetry as “imaginary gardens with real toads in them.” Dudley Herschbach further extends this metaphor to the sciences, depicting scientists as “gardeners of ideas” who create fruits and flowers of understanding, here implying information to transmit that understanding. “Such intellectual gardeners usually pay little attention to toads or other uninvited creatures residing among the flowers – unless those creatures begin to munch or trample the plants” (Herschbach 11). Visitors to the garden sometimes focus more on the toads than the flowers, even mistaking the gardeners for toads. Do information scientists concentrate too much on the toads in our own garden? The toads in our garden are not preventing gardening or growth. Does it really matter if the toads are there if the flowers still grow? Perhaps we should return our attention to the flowers and let the toads take care of themselves.
Bibliography
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Brookes, Bertram C. “The Foundations of Information Science: Part I. Philosophical Aspects.” Journal of Information Science 2 (1980): 125-133.
Buckland, Michael K. "Information as Thing," Journal of the American Society for Information Science 42 (June 1991): 351-360.
Herschbach, Dudley R. “Imaginary Gardens with Real Toads.” The Flight From Science and Reason. Ed. Paul R. Gross, Norman Levitt, and Martin W. Lewis. (New York: New York Academy of Sciences, 1997).
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Moore, Marianne. “Poetry.” http://eir.library.utoronto.ca/rpo/display/poem1488.html accessed April 16 2005.
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