This is the keynote presentation delivered at The Sixth Conference on Problem-Based Learning in Finland: Constructing Knowledge in information society, Tampere, 2006 June 6-7. Abstract: Finding information, especially accurate, timely, and relevant information, is increasingly important in nearly all human endeavors. Accordingly, numerous studies have examined the processes information seekers employ, as well as the strategies information providers use to meet their needs. Most models emphasize satisfaction or closure as the criterion for successful completion of an information search; thus the emphasis is on solving a specific problem. But often, information seeking is part of some larger process, which is invisible to the information provider and often unclear even to the seeker. Successful search may lead not so much to eliminating an existing, well-defined problem, as to delineating a new problem within a complex, ill-defined space. This paper examines information seeking from an inquiry, or problem-based perspective, and argues that the fields of information seeking and problem-based learning can benefit from closer dialogue.

Artificial Intelligence Lab, Department of MIS, University of Arizona / In response to the September 11 terrorist attacks, major government efforts to modernize federal law enforcement authorities’ intelligence collection and processing capabilities have been initiated. At the state and local levels, crime and police report data is rapidly migrating from paper records to automated records management systems in recent years, making them increasingly accessible. However, despite the increasing availability of data, many challenges continue to hinder effective use of law enforcement data and knowledge, in turn limiting crime-fighting capabilities of related government agencies. For instance, most local police have database systems used by their own personnel, but lack an efficient manner in which to share information with other agencies. More importantly, the tools necessary to retrieve, filter, integrate, and intelligently present relevant information have not yet been sufficiently refined. According to senior Justice Department officials quoted on MSNBC, Sept. 26, 2001, there is “justifiable skepticism about the FBI’s ability to handle massive amounts of information,” and recent anti-terrorism initiatives will create more data overload problems. As part of nationwide, ongoing digital government initiatives, COPLINK is an integrated information and knowledge management environment aimed at meeting some of these challenges.

This is Module 3 of the ICT for Library and Information Professionals (ICTLIP) Training Package for Developing Countries. This Package is intended to provide the knowledge and skills required to deal with the application of ICT to library and information services. It is meant for library and information personnel who may become trainers in the area. The Package has been developed by the UNESCO Asia & Pacific Regional Office with funding from the Japanese Fund in Trust for Communication and Information. It contains six modules: Module 1 - Introduction to Information and Communication Technologies Module 2 - Introduction to Integrated Library Systems Module 3 - Information Seeking in an Electronic Environment Module 4 - Database Design, and Information Storage and Retrieval Module 5 - The Internet as an Information Resource Module 6 - Web Page Concept and Design: Getting a Web Page Up and Running

Digital Library for Earth Science Education, DLESE / The focus of our project was to build functional prototype of the discovery system user interface (UI) for the Digital Library for Earth System Education (DLESE). The prototype had two goals: first to show a proof of concept for the DLESE project and second to provide an initial search and discovery implementation that can be extended to include multiple heterogeneous data collections in future iterations. Our design goal was to ensure that userâ s desired information be easy and convenient to discover via the UI. We focused on three components with this goal in mind: first a keyword search designed so that the most relevant information was returned at the top of the results list. Second a â browseâ search that provided a summary of the resource topology in one simple view. Third a clear and concise presentation of search results that allow users to evaluate desired information quickly. Once the prototype was up and running we conducted user tests. The results of these tests and our recommendations for future iterations of the DLESE search engine are outlined at the end of this report.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Valuable criminal-justice data in free texts such as police narrative reports are currently difficult to be accessed and used by intelligence investigators in crime analyses. It would be desirable to automatically identify from text reports meaningful entities, such as person names, addresses, narcotic drugs, or vehicle names to facilitate crime investigation. In this paper, we report our work on a neural network-based entity extractor, which applies named-entity extraction techniques to identify useful entities from police narrative reports. Preliminary evaluation results demonstrated that our approach is feasible and has some potential values for real-life applications. Our system achieved encouraging precision and recall rates for person names and narcotic drugs, but did not perform well for addresses and personal properties. Our future work includes conducting larger-scale evaluation studies and enhancing the system to capture human knowledge interactively.

"Copyright in all articles appearing in the Journal of the Medical Library Association is owned by their authors. Readers may copy articles without permission of the copyright owners, as long as the author and the Medical Library Association are acknowledged in the copy and the copy is used for educational, not-for-profit purposes." / Objectives: The purpose of this study is to assess whether recent graduates of the Ohio State University's Occupational Therapy division are applying information-seeking skills they learned as undergraduates, and to seek their advice on ways to improve information-literacy instruction for current and future occupational therapy students. Method: A survey was sent to a sample of graduates from 1995â 2000. The results were entered into an SPSS database, and descriptive and inferential results were calculated to determine the information-seeking patterns of these recent graduates. Results: A majority of the occupational therapy graduates who responded to the survey prefer to use information resources that are readily available to them, such as advice from their colleagues or supervisors (79%) and the Internet (69%), rather than the evidence available in the journal literature. Twenty-six percent (26%) of the graduates have searched MEDLINE or CINAHL at least once since they graduated. Formal library instruction sessions were considered useful by 42% of the graduates, and 22% of the graduates found informal contacts with librarians to be useful. Conclusions: Librarians and occupational therapy faculty must intensify their efforts to convey the importance of applying research information to patient care and inform students of ways to access this information after they graduate. In addition to teaching searching skills for MEDLINE and CINAHL, they must provide instruction on how to assess the quality of information they find on the Internet. Other findings suggest that occupational therapy practitioners need access to information systems in the clinical setting that synthesize the research in a way that is readily applicable to patient-care issues.

This is a presentation of 12 slides at GL7: Seventh International Conference on Grey Literature, Nancy, France. The presentation argues that distinction between grey and non-grey (or white) literature will become less relevant over time, as online discovery options proliferate. In the meantime, the political success of the open access publishing movement has valuable lessons for proponents of increasing access to grey literature.

Winner of the Association of Library and Information Science Education (ALISE) Research Methodology Best Paper in 2001 Award. Abstract: As research questions and topics in information studies evolve, there is a continual need to seek out innovative research methods to help us investigate and address these questions. This paper presents an emerging research method, the creation and analysis of information horizon maps, and discusses the use of such maps in an ongoing research study. Sonnenwald's (1999) framework for human information behavior provides a theoretical foundation for this method. This theoretical framework suggests that within a context and situation is an 'information horizon' in which we can act. Study participants are asked to describe several recent information seeking situations for a particular context, and to draw a map of their information horizon, graphically representing the information resources (including people) they typically access in this context and their preferences for the resources accessed. The resulting graphical representation of their information horizons are analyzed in conjunction with the interview data using a variety of techniques derived from social network analysis and content analysis. In this paper these techniques are described and illustrated using examples from an ongoing study of the information seeking behavior of lower socio-economic students. They are then compared to other techniques that could be used to gather data about people's information seeking behavior.

Artificial Intelligence Lab, Department of MIS, University of Arizona / The problems of information overload and vocabulary differences have become more pressing with the emergence of increasingly popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet WWW software are based on either keyword search (e.g., the Lycos server at CMU, the Yahoo server at Stanford) or hypertext browsing (e.g., Mosaic and Netscape). This research aims to provide an alternative concept-based categorization and search capability for WWW servers based on selected machine learning algorithms. Our proposed approach, which is grounded on automatic textual analysis of Internet documents (homepages), attempts to address the Internet search problem by first categorizing the content of Internet documents. We report results of our recent testing of a multilayered neural network clustering algorithm employing the Kohonen self-organizing feature map to categorize (classify) Internet homepages according to their content. The category hierarchies created could serve to partition the vast Internet services into subject-specific categories and databases and improve Internet keyword searching and/or browsing.

Artificial Intelligence Lab, Department of MIS, University of Arizona / In this era of the Internet and distributed multimedia computing, new and emerging classes of information technologies have swept into the lives of office workers and everyday people. As technologies and applications become more overwhelming, pressing, and diverse, several well-known information technology problems have become even more urgent. Information overload, a result of the ease of information creation and rendering via Internet and WWW, has become more evident in people’s lives. Significant variations of database formats and structures, the richness of information media text, audio, and video , and an abundance of multilingual information content also have created various information interoperability problems - structural interoperability, media interoperability, and multilingual interoperability.