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There has been a massive investment in the installation of online catalogs: in selection, in the supporting infrastructure of terminals and networks, in catalog record conversion, in training, and, lately, in linking online catalogs with other online systems. In contrast, the state‐of‐the‐art of the functionality of online library catalogs has advanced little in the past few years. Rather it has been a matter of existing systems being upgraded towards the functionality of the better systems and of refinements being added. It is time for a further advance in online catalog design. We believe that the next generation of online catalogs should and will have features such as those discussed and illustrated in this article.

This article examines the structure and components of information storage and retrieval systems and information filtering systems. Analysis of the tasks performed in such selection systems leads to the identification of 13 components. Eight are necessarily present in all such systems, mechanized or not; the others may, but need not be, present. The authors argue that all selection systems can be represented in terms of combinations of these components. The components are of only two types: representations of data objects and functions that operate on them. Further, the functional components, or rules, reduce to two basic types: 1) transformation, making or modifying the members of a set of representations, and 2) sorting or partitioning. The representational transformations may be in the form of copies, excerpts, descriptions, abstractions, or mere identifying references. By partitioning, we mean dividing a set of objects by using matching, sorting, ranking, selecting, and other logically equivalent operations. The typical multiplicity of knowledge sources and of system vocabularies is noted. Some of the implications for the study, use, and design of information storage and retrieval systems are discussed.

What kind of knowledge is needed by information specialists working in a specific subject field like medicine, sociology or music? What approaches have been used in information science to produce kinds of domain‐specific knowledge? This article presents 11 approaches to domain analysis. Together these approaches make a unique competence for information specialists. The approaches are: producing literature guides and subject gateways; producing special classifications and thesauri; research on indexing and retrieving specialities; empirical user studies; bibliometrical studies; historical studies; document and genre studies; epistemological and critical studies; terminological studies, LSP (languages for special purposes), discourse studies; studies of structures and institutions in scientific communication; and domain analysis in professional cognition and artificial intelligence. Specific examples and selective reviews of literature are provided, and the strengths and drawbacks of each of these approaches are discussed.