This item is not the definitive copy. Please use the following citation when referencing this material: Mostafa, J. and Dillon, A. (1996) Design and Evaluation of a User Interface Supporting Multiple Image Query Models. Proceedings of the 59th Annual Conference of the American Society for Information Science, Baltimore, MD, USA, October 21-26, 1996. I. Introduction: Digital image use occurs in many fields. For example, in the area of medicine, huge volumes of digital images are routinely generated for diagnostic purposes, sometimes reaching gigabyte range (Gitlin, 1992). Besser (1990) has designed highly innovative image- based selection systems to improve access to visual resources in architecture, anthropology and art collections. There are also signs that museums and archives have accepted the value of digital image technology in their environments (Besser, 1991; Wentz, 1989). Unfortunately, the technology for effective storage and retrieval of images has not kept pace with the technology of image production. The situation has reached such a critical stage that National Science Foundation (NSF) organized a special workshop on the topic of visual information management (Jain, 1993). The NSF workshop report stated, "It would be impossible to cope with this explosion of image information, unless the images were organized for retrieval. The fundamental problem is that images, video, and other similar data differ from numeric data and text data format, and hence they require a totally different technique of organization, indexing and query processing." This paper addresses the critical need for different techniques in improving retrieval of digital images. Our position is that the user interface is the principal component responsible for facilitating retrieval in databases. Therefore, to assure effective access design of interfaces need to be improved.

The Institute for Scientific Information's (ISI) citation databases have been used for decades as a starting point and often as the only tools for locating citations and/or conducting citation analyses. ISI databases (or Web of Science [WoS]), however, may no longer be sufficient because new databases and tools that allow citation searching are now available. Using citations to the work of 25 library and information science faculty members as a case study, this paper examines the effects of using Scopus and Google Scholar (GS) on the citation counts and rankings of scholars as measured by WoS. Overall, more than 10,000 citing and purportedly citing documents were examined. Results show that Scopus significantly alters the relative ranking of those scholars that appear in the middle of the rankings and that GS stands out in its coverage of conference proceedings as well as international, non-English language journals. The use of Scopus and GS, in addition to WoS, helps reveal a more accurate and comprehensive picture of the scholarly impact of authors. WoS data took about 100 hours of collecting and processing time, Scopus consumed 200 hours, and GS a grueling 3,000 hours.

SIPP ACCESS represents an innovation in providing services for statistical data. A computer-based, integrated information system incorporates both the data and information about the data. SIPP ACCESS systematically links the technologies of laser disk, mainframe computer, microcomputer, and electronic networks and applies relational technology to create great efficiencies and lower the costs of storing, managing, retrieving, and transmitting data and information about complex statistical data collections. This information system has been applied to national longitudinal panel surveys. The article describes the reasons why SIPP ACCESS was created to improve access to these complex surveys and provides examples of tools that facilitate access to information about the contents of these large data sets.

“What does the global research environment look like?” This paper presents a summary look at the results of efforts to address this question using available indicators on global research production. It was surprising how little information is available, how difficult some of it is to access and how flawed the data are. The three most useful data sources were UNESCO (United Nations Educational, Scientific and Cultural Organization) Research and Development data (1996-2002), the Institute of Scientific Information publications listings for January 1998 through March 2003, and the World of Learning 2002 reference volume. The data showed that it is difficult to easily get a good overview of the global research situation from existing sources. Furthermore, inequalities between countries in research capacity are marked and challenging. Information science offers strategies for responding to both of these challenges. In both cases improvements are likely if access to information can be facilitated and the process of integrating information from different sources can be simplified, allowing transformation into effective action. The global research environment thus serves as a case study for the focus of this paper – the exploration of information science responses to challenges in the management, exchange and implementation of knowledge globally.

This paper revises David Ellis's information-seeking behavior model of social scientists, which includes six generic features: starting, chaining, browsing, differentiating, monitoring, and extracting. The paper uses social science faculty researching stateless nations as the study population. The description and analysis of the information-seeking behavior of this group of scholars is based on data collected through structured and semistructured electronic mail interviews. Sixty faculty members from 14 different countries were interviewed by e-mail. For reality check purposes, face-to-face interviews with five faculty members were also conducted. Although the study confirmed Ellis's model, it found that a fuller description of the information-seeking process of social scientists studying stateless nations should include four additional features besides those identified by Ellis. These new features are: accessing, networking, verifying, and information managing. In view of that, the study develops a new model, which, unlike Ellis's, groups all the features into four interrelated stages: searching, accessing, processing, and ending. This new model is fully described and its implications on research and practice are discussed. How and why scholars studied here are different than other academic social scientists is also discussed.

The purpose of this article is to contribute to our stock of knowledge about who uses networks, how they are used, and what contribution the networks make to advancing the scientific enterprise. Between 1985 and 1990, the Survey of Income and Program Participation (SIPP) ACCESS data facility at the University of Wisconsin-Madison provided social scientists in the United States and elsewhere with access through the electronic networks to complex and dynamic statistical data; the 1984 SIPP is a longitudinal panel survey designed to examine economic well-being in the United States. This article describes the conceptual framework and design of SIPP ACCESS; examines how network users communicated with the SIPP ACCESS project staff about the SIPP data; and evaluates one outcome derived from the communications, the improvement of the quality of the SIPP data. The direct and indirect benefits to social scientists of electronic networks are discussed. The author concludes with a series of policy recommendations that link the assessment of our inadequate knowledge base for evaluating how electronic networks advance the scientific enterprise and the SIPP ACCESS research network experience to the policy initiatives of the High Performance Computing Act of 1991 (P.L. 102-194) and the related extensive recommendations embodied in Grand Challenges 1993 High Performance Computing and Communications (The FY 1993 U.S. Research and Development Program).

Grand challenges such as public health, security, genomics, environmental protection, education, and economics, are characterized by complexity, interdependence, globalization, and unpredictability. Although the unprecedented quantity of information surrounding these challenges can provide users with a new perspective on solutions, the data surrounding complex systems vary with respect to levels of structure and authority, and include vastly different contexts and vocabularies. To be successful in this domain we must extend our models of information science such that they operate successfully in environments where the quantity of relevant information far exceeds our human processing capacity. For example, the well-accepted precision and recall metrics break down when hundreds of thousands of documents are relevant. Solutions to grand challenges require that information scientists shift their focus from information retrieval towards information synthesis.

Reports results of a study to explore how well six popular Web search engines performed in retrieving specific electronic finding aids mounted on the World Wide Web. A random sample of online finding aids was selected and then searched using AltaVista, Excite, Fast Search, Google, Hotbot and Northern Light, employing both word and phrase searching. As of February 2000, approximately 8 percent of repositories listed at the 'Repositories of Primary Resources' Web site had mounted at least four full finding aids on the Web. The most striking finding of this study was the importance of using phrase searches whenever possible, rather than word searches. Also of significance was the fact that if a finding aid were to be found using any search engine, it was generally found in the first ten or twenty items at most. The study identifies the best performers among the six chosen search engines. Combinations of search engines often produced much better results than did the search engines individually, evidence that there may be little overlap among the top hits provided by individual engines.

This study evaluates the data sources and research methods used in earlier studies to rank the research productivity of Library and Information Science (LIS) faculty and schools. In doing so, the study identifies both tools and methods that generate more accurate publication count rankings as well as databases that should be taken into consideration when conducting comprehensive searches in the literature for research and curricular needs. With a list of 2,625 items published between 1982 and 2002 by 68 faculty members of 18 American Library Associationâ (ALA-) accredited LIS schools, hundreds of databases were searched. Results show that there are only 10 databases that provide significant coverage of the LIS indexed literature. Results also show that restricting the data sources to one, two, or even three databases leads to inaccurate rankings and erroneous conclusions. Because no database provides comprehensive coverage of the LIS literature, researchers must rely on a wide range of disciplinary and multidisciplinary databases for ranking and other research purposes. The study answers such questions as the following: Is the Association of Library and Information Science Educationâ s (ALISEâ s) directory of members a reliable tool to identify a complete list of faculty members at LIS schools? How many and which databases are needed in a multifile search to arrive at accurate publication count rankings? What coverage will be achieved using a certain number of databases? Which research areas are well covered by which databases? What alternative methods and tools are available to supplement gaps among databases? Did coverage performance of databases change over time? What counting method should be used when determining what and how many items each LIS faculty and school has published? The authors recommend advanced analysis of research productivity to provide a more detailed assessment of research productivity of authors and programs.

In recent decades there has been a notable expansion of statistical data produced by the public and private sectors for administrative, research, policy and evaluation programmes. This is due to advances in relatively inexpensive and efficient data collection and management of computer-readable statistical data. Corresponding changes have not occurred in the management of data collection, preservation, description and dissemination. As a result, the process by which data become accessible to social researchers and others is frustrating, time consuming, and inefficient. This paper describes the reasons for this situation: the problem-solving workstyle of social data users, the nature of the data and their relationship to computer technology, and an inchoate social science information infrastructure. Since statistical data play an increasingly important role in social research and policy decisions, social science information specialists must be prepared to meet the computer-readable statistical data user's needs. Four strategies are recommended for improving utilization of these data: improving the quality of statistical evidence, educating information professionals and end-users in numerical information, using the existing information infrastructure to preserve and disseminate data, and developing retrieval tools for improving access to information about social data.