This article is a programmatic article, which formulates a new approach to information science (IS): domain‐analysis. This approach states that the most fruitful horizon for IS is to study the knowledge‐domains as thought or discourse communities, which are parts of society's division of labor. The article is also a review article, providing a multidisciplinary description of research, illuminating this theoretical view. The first section presents contemporary research in IS, sharing the fundamental viewpoint that IS should be seen as a social rather than as a purely mental discipline. In addition, important predecessors to this view are mentioned and the possibilities as well as the limitations of their approaches are discussed. The second section describes recent transdisciplinary tendencies in the understanding of knowledge. In bordering disciplines to IS, such as educational research, psychology, linguistics, and the philosophy of science, an important new view of knowledge is appearing in the 1990s. This new view of knowledge stresses the social, ecological, and content‐oriented nature of knowledge. This is opposed to the more formal, computer‐like approaches that dominated in the 1980s. The third section compares domain‐analysis to other major approaches in IS, such as the cognitive approach. The final section outlines important problems to be investigated, such as how different knowledge‐domains affect the informational value of different subject access points in data bases. © 1995 John Wiley & Sons, Inc.

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This article presents a socio-cognitive perspective in relation to information science (IS) and information retrieval (IR). The differences between traditional cognitive views and the socio-cognitive or domain-analytic view are outlined. It is claimed that, given elementary skills in computer-based retrieval, people are basically interacting with representations of subject literatures in IR. The kind of knowledge needed to interact with representations of subject literatures is discussed. It is shown how different approaches or "paradigms" in the represented literature imply different information needs and relevance criteria (which users typically cannot express very well, which is why IS cannot primarily rely on user studies). These principles are exemplified by comparing behaviorism, cognitivism, psychoanalysis, and neuroscience as approaches in psychology. The relevance criteria implicit in each position are outlined, and empirical data are provided to prove the theoretical claims. It is further shown that the most general level of relevance criteria is implied by epistemological theories. The article concludes that the fundamental problems of IS and IR are based in epistemology, which therefore becomes the most important allied field for IS.

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It cannot be overemphasized that changes in concepts have far more impact than new discoveries (Mayr, 1997, p. 98) Concept theory is an extremely broad, interdisciplinary and complex field of research related to many deep fields with very long historical traditions without much consensus. However, information science and knowledge organization cannot avoid relating to theories of concepts. Knowledge organizing systems (e.g., classification systems, thesauri, and ontologies) should be understood as systems basically organizing concepts and their semantic relations. The same is the case with information retrieval systems. Different theories of concepts have different implications for how to construe, evaluate, and use such systems. Based on "a post-Kuhnian view" of paradigms, this article put forward arguments that the best understanding and classification of theories of concepts is to view and classify them in accordance with epistemological theories (empiricism, rationalism, historicism, and pragmatism). It is also argued that the historicist and pragmatist understandings of concepts are the most fruitful views and that this understanding may be part of a broader paradigm shift that is also beginning to take place in information science. The importance of historicist and pragmatic theories of concepts for information science is outlined.