Hypothesis: IS is broad and is essentially multidisciplinary
That the disciplines have their own perspectives, questions, solutions to part of IS
That there’s tuff disputes
Conclusion: LIS is broad, too,
-----
What is information science today?
Draft thoughts on the history of information science and research opportunities in LIS today.
Not for distribution.
G. Benoit, Simmons College, GSLIS.
In 1967, the American Documentation Institute voted to change its name to the
American Society for Information Science. This change prompted people to consider an equal shift in identity: just what is information science? In January of 1968, Harold
Borko, a scientist working at System Development Corporation, a precursor to the RAND
Corp., asked “Information Science: what is it?” (Borko, 1968). His conclusion was that the subject of information was all-encompassing, and so a definition of information science was going to be equally all-encompassing:
“ Information science is that discipline that investigates the properties and behavior of information, the forces governing the flow of information, and the means of processing information for optimum accessibility and usability. it is concerned with that body of knowledge relating to the origination, collection, organization, storage, retrieval, interpretation, transmission, transformation, and utilization of information. This includes the investigation of information representations in both natural and artificial systems, the use of codes for efficient message transmission, and the study of information processing devices and techniques such as computers and their programming systems. It is an interdisciplinary science derived from and related to such fields as mathematics, logic, linguistics, psychology, computer technology, operations research, the graphic arts, communications, library science, management, and other similar fields. It has both a purse science component, which inquires into the subject without regard to its application, and an applied science component, which develops services and products” (Borko, 1968, 3).
The motivation for the change in identity and the all-encompassing definition is found then, as today, in changes in how representations of knowledge are stored, made available, interpreted, and integrated into people’s lives and work. Borko saw, although he didn’t state it this way, that people’s understanding , based on a foundation of knowledge, framed how they saw the world and interacted with it. When we reflect on the 1960s we see he was right: social upheavals here and abroad, terrifically increased access to resources (schools, libraries, newspapers, but also expansion of radio to include
AM
and
FM
, as well as increased television ownership). In other words, “working knowledge” changed frequently and people needed to keep up.
The technical underpinnings of distributing access to resources, too, changed dramatically. Television is an example of the physical channel from source to receiver; there was also a huge increase in scientific journals and conferences. Needless to say, the greatest evolution had arrived – the computer – and was being integrated in business situations, from its original home in the sciences.
Three Movements
Information science was, and some may say still is, trying to reach all aspects of human interaction with physical forms of knowledge. IS originally did not incorporate

issues of human cognition: the human consumer of the data from the resource left the view of IS for some other vista, such as education or literature studies. What IS looked at was the object : the book, the computer file, the database. Ultimately, this lead IS to peer deeply into the structure of the representation.
IBM and the birth of full-text retrieval There are many impetuses at play but we’ll look at only three. First is the arrival of the computer as a powerful storage, retrieval and communication channel for those objects. His employer, IBM, had a machine that needed a purpose: Hans-Peter Luhn, a researcher, found one. Luhn observed that a machine that holds all the words of a document really is holding symbols : all that was lacking was an algorithm that would match these symbols to something people wanted: information. By comparing how people conceptualize ideas, in the form of keywords, he would match the idea to a physical document. The actual matching would be a mathematical formula, an algorithm, that compared the user’s keyword (the query) to a numeric representation of the frequency of a term appearing either within the context or without the context. In other words, he developed KWIC and KWOC. There was, therefore, a [then] powerful machine for symbol manipulation and a store of symbols to be manipulated (documents). This is the foundation for full-text retrieval.
Scientific environment You’ve likely seen the movie “Desk Set” with Katharine
Hepburn and Spencer Tracy. In the film, a company wants to introduce a computer into the reference library. The staff, lead by Hepburn, naturally resists, thinking they’re going to be fired, and so do all they can to make the machine fail. Spencer Tracy’s character, an efficiency expert, ultimately explains that the machine is supposed to help the reference librarians in their work. In the course of the movie, the librarians demonstrated both a vast knowledge of facts and how and where to find other facts. The machine could process questions, too, but the questions had to be semantically unambiguous.
The movie was released in the same era that had people afraid of technology (the
“duck-and-cover” films of how kids could avoid being vaporized during a nuclear blast), socially fearful of technology (the Soviet space program), while at the same time enjoying the benefits of technology, the countless ads for home labor saving devices. In
1960s, there was considerable government spending on technology, especially working collaboratively with universities (History of Information Science; Clough, 2003;
[funding]). The foundation of the 60s lead to that of the 1970s and DARPAnet, the ultimate example of government-university interaction: the Defense Department’s distributed computer technology for storing, sharing, and communicating documents.
[Yes, this is the forerunner of the Internet as we know it today.]
This movie, spending, love-hate relationship of people to technology suggest how science and technology the social environment was prepared to accept changes in the public conception of the format, storage, retrieval, and use of the objects of knowledge.
Areas of Work It is perhaps for these reasons that Borko cites another report of 655 projects in the nascent IS, which he categories into 9 groups:
1.
information needs and uses [behavioral studies of users; citation studies; communication patterns; literature use studies]
2.
document creation and copying [computer-assisted composition, …, writing and editing]
3.
language analysis [computational linguistics; lexicography; natural language
(text) processing; psycholinguistics; semantic analysis]

4.
translation [machine translation; translation aids]
5.
abstracting, classification, coding and indexing [classification and indexing systems; content analysis; machine-aided classification; extracting and indexing; vocabulary studies]
6.
system design [information centers; information retrieval; mechanization of library operations; selective dissemination of information]
7.
analysis and evaluation [comparative studies; indexing quality; modeling; test methods and performance measures; translation quality]
8.
pattern recognition [image processing; speech analysis]
9.
adaptive systems [artificial intelligence; automata; problem solving; selforganizing systems]
(Borko, 1968, p. 4). Some of these work areas would be traditionally considered librarianship. Some fall into mathematics, logic, and language. Others were rather forward-looking and prescient, such as adaptive systems.
On the heels of Borko’s paper, C. J. Date published the fundamental model of database design today. Date worked out a complete relational algebra that could be used in a symbol manipulating machine. [See a trend?] The door to a warehouse of storage, access, and communication possibilities was to be unlocked by these two trends: full-text and now relational database management systems.
Librarianship goes a different direction The third major trend in the 1960s affecting and helping to define IS was a shift in librarianship’s view of itself and its role in turbulent 1960’s. Baldwin (----) describes the fight for the adoption of the Library Bill of Rights. In his article, he asks that if “libraries are forums for information and ideas”, then “for whom, and for what?” He asks whether the case can be made for viewing the library as a forum for the production and reproduction of culture. Can we view the library as an institution in and through which ideology flows, is produced, and is perpetuated? Berninghausen (1972), and others, saw the BoR as a means to “codify and standardize a purist moral stance on intellectual freedom by which impartiality and neutrality on nonliterary issues served as the central principle of the profession” (Samek,
1966). The neutral stance meant the library was threatened by the political right and the left. Wedgeworth et al. (1973, p. 33) argued that the library’s role in social issues was akin to the civil rights movement, a “rallying point for social action”. As Glassing, 1970, p. 11) notes, library leaders felt the public was tired of “social and political indifference” and “bitter about a government ‘incapable of solving racial and poverty problems in the world’s wealthiest nation”. In short, most of the public library movement had embraced social responsibility. With that, it appears, came a shunning of technology, but a commitment to the people’s access to resources. An entirely untested thesis is that as companies moved into text storage and processing, along with the dramatic rise in data base theory, libraries moved from part of their traditional functions associated with storage and retrieval and so missed a partnership opportunity that only in the past 10-15 years (CHECK) is being addressed with the inclusion of “information science” in the library science curriculum.
IS as Multidisciplinary Endeavor
From Borko’s first definition, he concludes with a briefer definition, in which the many work areas of information science can be subsumed: information science is “an interdisciplinary science that investigates the properties and behavior of information, the

forces that govern the flow and use of information, and the techniques, both manual and mechanical, of processing information for optimal storage, retrieval, and dissemination”
(Borko, 1968, p. 5). This definition is workable and informative because it emphasizes the vast influence that accessed data can have on people, the shift from the 1960s of the “scientific” investigation into the processes associated with accessing data, the expectations that language used to express data (documents), the language used to request data (queries) and their meeting (retrieval algorithms, reference interview) can and should be expressed from perspective of symbol manipulation (that is, something a machine can determine), along with, perhaps, the social, political, and technical issues “governing the flow and use of information.”
If we examine this definition further, we see many more opportunities, depending on one’s domain of research or work. The computer scientist will jump on the idea of
“optimal” storage and retrieval; … [more]
Types of IS
From engineering:
Future
Bates’s thoughts on IS
Particular emphasis is given to information science's role as a meta-science -- conducting research and developing theory around the documentary products of other disciplines and activities. The mental activities of the professional practice of the field are seen to center around representation and organization of information rather than knowing information. It is argued that such representation engages fundamentally different talents and skills from those required in other professions and intellectual disciplines. Methodological approaches and values of information science are also considered.
Saracevic: evolved over the past half-century. Various sections examine the origin of information science in respect to the problems of information explosion; the social role of the field; the nature of "information" in information science; the structure of the field in terms of problems addressed; evolutionary trends in information retrieval as a major branch of information science; the relation of information science to other fields, most notably librarianship and computer science; and educational models and issues. Conclusions explore some dominant trends affecting the field.
White & McCain: This study presents an extensive domain analysis of a discipline - information science - in terms of its authors.
Names of those most frequently cited in 12 key journals from 1972 through 1995 were retrieved from Social Scisearch via DIALOG. The top 120 were submitted to author co-citation analyses, yielding

automatic classifications relevant to histories of the field.
Tables and graphics reveal: (1) The disciplinary and institutional affiliations of contributors to information science; (2) the specialty structure of the discipline over 24 years; (3) authors' memberships in 1 or more specialties; (4) inertia and change in authors' positions on 2-dimensional subject maps over 3 8-year subperiods, 1972-1979, 1980-1987, 1988-1995;
(5) the 2 major subdisciplines of information science and their evolving memberships; (6) canonical authors who are in the top
100 in all three subperiods; (7) changes in authors' eminence and influence over the subperiods, as shown by mean co-citation counts; (8) authors with marked changes in their mapped positions over the subperiods; (9) the axes on which authors are mapped, with interpretations; (10) evidence of a paradigm shift in information science in the 1980s; and (11) evidence on the general nature and state of integration of information science.
Statistical routines include ALSCAL, INDSCAL, factor analysis, and cluster analysis with SPSS; maps and other graphics were made with DeltaGraph. Theory and methodology are sufficiently detailed to be usable by other researchers.
Hawkins: This article continues earlier research on the development of a new definition of the field of information science and the creation of a "map" of the field showing subjects central to it and their relationships to those on the periphery. A case study describes the creation of a new classification structure
(taxonomy) for the Information Science Abstracts (ISA) database,
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