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Members of the Modern Language Association of America (MLA) were surveyed about their use of computer-based tools. A questionnaire was sent to 1,000 randomly-selected members in the U.S., with 500 sent via paper mail and 500 through electronic mail. Word processing, electronic mail, on-line catalogs, and the MLA International Bibliography were used heavily. Responses by the two subgroups differed significantly in several respects. Electronic full texts received substantially less use by both groups, especially those responding to the print survey. Major changes in research habits included greater reliance on word processing and more work outside of libraries. Problems reported focused on access to computer-based resources, learning to use them, the need for instruction, and inconsistent interfaces. Finally, evidence strongly suggests that reliance solely on electronic surveys may produce misleading results. © 1996 John Wiley & Sons, Inc.

In a previous paper from The Wellcome Foundation (Scott et al., 1971) a technique was described for measuring the usefulness of a commercial data base by comparing the choice of papers and of indexing terms to those chosen as relevant to the organization. In this second paper we are comparing the cost effectiveness of several commercial data bases, journal scanning by information scientists, and the impact of private communication.

This paper has a dual character dictated by its twofold purpose. First, it is a speculative historiographic essay containing an attempt to fix the present position of library and information science within the context of the probabilistic revolution that has been encompassing all of science. Second, it comprises a guide to practitioners engaged in statistical research in library and information science. There are pointed out the problems of utilizing statistical methods in library and information science because of the highly and positively skewed distributions that dominate this discipline. Biostatistics are indicated as the source of solutions for these problems, and the solutions are then traced back to the British biometric revolution of 1865‐1950, during the course of which modern inferential statistics were created. The thesis is presented that science has been undergoing a probabilistic revolution for over 200 years, and it is stated that this revolution is now coming to library and information science, as general stochastic models replace specific, empirical informetric laws. An account is given of the historical development of the counting distributions and laws of error applicable in statistical research in library and information science, and it is stressed that these distributions and laws are not specific to library and information science but are inherent in all biological and social phenomena. Urquhart’s Law is used to give a practical demonstration of the distributions. The difficulties of precisely fitting data to theoretical probability models in library and information science because of the inherent fuzziness of the sets are discussed, and the paper concludes with the description of a simple technique for identifying and dealing with the skewed distributions in library and information science. Throughout the paper, emphasis is placed on the relevance of research in library and information science to social problems, both past and present.

Evaluation in information retrieval (IR) has focussed largely on noninteractive evaluation of text retrieval systems. This is increasingly at odds with how people use modern IR systems: in highly interactive settings to access linked, multimedia information. Furthermore, this approach ignores potential improvements through better interface design. In 1996 the Commission of the European Union Information Technologies Programme, funded a three year working group, Mira, to discuss and advance research in the area of evaluation frameworks for interactive and multimedia IR applications. Led by Keith van Rijsbergen, Steve Draper and myself from Glasgow University, this working group brought together many of the leading researchers in the evaluation domain from both the IR and human computer interaction (HCI) communities. This paper presents my personal view of the main lines of discussion that took place throughout Mira: importing and adapting evaluation techniques from HCI, evaluating at different levels as appropriate, evaluating against different types of relevance and the new challenges that drive the need for rethinking the old evaluation approaches. The paper concludes that we need to consider more varied forms of evaluation to complement engine evaluation.

This paper begins to identify and characterize the knowledge used by experienced librarians while searching for subject information in online catalogs. Ten experienced librarians performed the same set of six subject searches in an online catalog. Investigated was the knowledge used to solve retrieval problems. This knowledge represents expertise in the use of the catalog. Data were collected through the use of think-aloud protocols, transaction logs, and structured interviews. Knowledge was defined as knowledge of objects (factual knowledge), knowledge of events (experiential knowledge), knowledge of performance (process knowledge), and metaknowledge. Metaknowledge is the sense of whole derived from the integration of factual, process, and experiential knowledge about the search and the conditions under which it is performed. The focus of this paper is on metaknowledge. For evidence of metaknowledge the data were examined for explanations that participants gave for their actions and observations, and for ways that participants evaluated their own progress during the process of searching. Reasons and explanations given by searchers were related to all phases of the library information retrieval process from the user's receipt of material to policies for collection development, and not just events directly related to the performance of a particular search task.

The pressures of limited budgets and of increased competition for use of funds are forcing information centers and libraries to initiate user fees. There have been, however, few precedents or guidelines to which the information service administrator might turn for assistance in formulating pricing policy. In this paper, components of the pricing decision are identified: the pricing objectives pursued, the pricing policies these aims are translated into, and the actual pricing methods employed in calculating what price to charge. A variety of pricing methods can be used to meet a given pricing objective, and several of these pricing practices are described using a basic classification scheme developed for the field of marketing: cost-oriented, competition-oriented, and demand-oriented approaches to pricing. Costs represent a starting point for developing pricing structure, and cost-oriented pricing techniques are taken up in detail. Cost functions are identified and their impact on price setting is suggested. Examples and data are provided from recent research into the pricing of computer-assisted selective dissemination of information (SDI) services. The techniques of price discrimination, marginal cost pricing, and break-even analysis are discussed. In making policy decisions, the need for accurate and complete cost data and demand information is emphasized, and several common approaches to estimating demand elasticity are suggested. The paper ends with a brief enumeration of sources of models to be explored for their applicability to the pricing of information services.

The shift towards the use of electronic media in scholarly communication appears to be an inescapable imperative. However, these shifts are uneven, both with respect to field and with respect to the form of communication. Different scientific fields have developed and use distinctly different communicative forums, both in the paper and electronic arenas, and these forums play different communicative roles within the field. One common claim is that we are in the early stages of an electronic revolution, that it is only a matter of time before other fields catch up with the early adopters, and that all fields converge on a stable set of electronic forums. A social shaping of technology (SST) perspective helps us to identify important social forces centered around disciplinary constructions of trust and of legitimate communication that pull against convergence. This analysis concludes that communicative plurality and communicative heterogeneity are durable features of the scholarly landscape, and that we are likely to see field differences in the use of and meaning ascribed to communications forums persist, even as overall use of electronic communications technologies both in science and in society as a whole increases., Comment: Accepted for publication in the Journal of the American Society for Information Science. Version was reformatted with several minor text changes

User problems with large information spaces multiply in complexity when we enter the digital domain. Virtual information environments can offer 3D representations, reconfigurations, and access to large databases that may overwhelm many users' abilities to filter and represent. As a result, users frequently experience disorientation in navigating large digital spaces to locate and use information. To date, the research response has been predominantly based on the analysis of visual navigational aids that might support users' bottom-up processing of the spatial display. In the present paper, an emerging alternative is considered that places greater emphasis on the top-down application of semantic knowledge by the user gleaned from their experiences within the sociocognitive context of information production and consumption. A distinction between spatial and semantic cues is introduced, and existing empirical data are reviewed that highlight the differential reliance on spatial or semantic information as the domain expertise of the user increases. The conclusion is reached that interfaces for shaping information should be built on an increasing analysis of users' semantic processing.

This paper describes ethnomethodologically informed ethnography (EM) as a methodology for information science research, illustrating the approach with the results of a study in a university library. We elucidate major differences between the practical orientation of EM and theoretical orientation of other ethnographic approaches in information science research. We address ways in which EM may be used to inform systems design and consider the issues that arise in coordinating the results of this research with the needs of information systems designers. We outline our approach to the “ethnographically informed” development of information systems in addressing some of the major problems of interdisciplinary work between system designers and EM researchers.

Information retrieval, workflow, collaborative filtering, and the path model can be considered as members of the family of approaches to information access. Although details of nomenclature and technique may vary, each is meant to provide people with access to useful information. In this paper we take a broad view over information access, drawing from philosophy and semiology in constructing a framework for comparative discussion. We use this framework to examine the information representations that underlie these four approaches, looking at phenomena included and excluded, the sharing of information amongst the community of use, interaction in terms of models of user activity and presentation of results, adaptation of system behaviour, and the inter-relationships of the representation's components. With deeper understanding of relative strengths and weaknesses, and characteristic emphases and assumptions, we can improve our selection, combination, and development of information systems.

This paper presents a framework for knowledge discovery and concept exploration. In order to enhance the concept exploration capability of knowledge-based systems and to alleviate the limitations of the manual browsing approach, we have developed two spreading activation-based algorithms for concept exploration in large, heterogeneous networks of concepts (e.g., multiple thesauri). One algorithm, which is based on the symbolic AI paradigm, performs a conventional branch-and-bound search on a semantic net representation to identify other highly relevant concepts (a serial, optimal search process). The second algorithm, which is based on the neural network approach, executes the Hopfield net parallel relaxation and convergence process to identify “convergent” concepts for some initial queries (a parallel, heuristic search process). Both algorithms can be adopted for automatic, multiple-thesauri consultation. We tested these two algorithms on a large text-based knowledge network of about 13,000 nodes (terms) and 80,000 directed links in the area of computing technologies. This knowledge network was created from two external thesauri and one automatically generated thesaurus. We conducted experiments to compare the behaviors and performances of the two algorithms with the hypertext-like browsing process. Our experiment revealed that manual browsing achieved higher-term recall but lower-term precision in comparison to the algorithmic systems. However, it was also a much more laborious and cognitively demanding process. In document retrieval, there were no statistically significant differences in document recall and precision between the algorithms and the manual browsing process. In light of the effort required by the manual browsing process, our proposed algorithmic approach presents a viable option for efficiently traversing large-scale, multiple thesauri (knowledge network). © 1995 John Wiley & Sons, Inc.

Results from research in information retrieval suggest that significant improvements in retrieval effectiveness could be obtained by combining results from multiple index representations and query strategies. Recently, an inference network based probabilistic retrieval model has been proposed, which views information retrieval as an evidential reasoning process in which multiple sources of evidence about document and query content are combined to estimate the relevance probabilities. In this paper we report a series of experiments we conducted using a specific implementation of this model to study the retrieval effectiveness of combining manaul and automatic index representations in queries and documents. The results indicate that significant benefits in retrieval effectiveness can be obtained through combined representations.

The exact Bradford distribution fits data on the scatter of articles in a given specialty among journals remarkably well, perhaps better than the approximate form of the distribution. This implies certain tendencies of authors in the specialty to distribute their future articles among the journals, on the basis of the past productivity (the number of articles previously published) of the journals. In particular it is shown that if this tendency follows a Bradford law for each group of journals with a given past productivity, then the distribution of papers among all the journals active in the specialty must also follow the exact Bradford distribution. Conversely, since this distribution does fit the data, it implies that the authors' tendencies also are Bradford. The consequences, when the statistical situation is fairly constant with time, are explored. Applications to citation scattering also are discussed.