This version of the report contains a hyperlinked table of contents to improve navigation. / This report describes the results of an Institute of Museum and Library Services (IMLS) funded study to investigate the use of technological or policy tools to control patron access to or use of digital collections of cultural materials created by U.S. archives, libraries and museums. The technological and policy tools serve primarily to control copying or other reuses of digital materials. The study had the following goals: 1. Assess what technical and policy tools cultural institutions are employing to control access to and use of online digital collections. 2. Investigate motivations for controlling access to or use of collections (e.g., copyright, privacy, protecting traditional restrictions, income generation etc.). 3. Investigate discouragers to the implementation of access and use control systems (e.g., preference for open collections, lack of resources, institutional mission, etc.). 4. Gauge interest in implementing technical systems to control access to and use of collections. 5. Determine what types of assistance IMLS could provide. 6. Identify institutions with innovative controlled online collections for follow up case studies on policy, technical and managerial details.

Many digital news archive systems in Taiwan are based on format description, not subject indexing. This requires users to know their background or the terminologies used, in order to retrieve information from these archives. This paper discusses how the original elements were indexed from various perspectives in Chinese digitized news archives. It also makes recommendations to improve the industry, including strengthening the process, connection, and description of news contents, organization, and management. This will enable cross-system retrieval and in-depth resource integration among systems.

Artificial Intelligence Lab, Department of MIS, University of Arizona / In this era of the Internet and the World Wide Web, the long-time topic of digital libraries has suddenly become white hot. As the Internet expands, particularly the WWW, more people are recognizing the need to search indexed collections. Digital library research projects thus have a common theme of bringing search to the Net. This is why the US government made digital libraries the flagship research effort for the National Information Infrastructure (NII), which seeks to bring the highways of knowledge to every American. As a result, the four-year, multiagency DLI was funded with roughly $1 million per year for each project (see the "Agency perspectives" sidebar). Six projects (chosen from 73 proposals) are involved in the DLI, which is sponsored by the National Science Foundation, Advanced Research Projects Agency, and the National Aeronautics and Space Administration. This issue of Computer includes project reports from these six university sites: Carnegie Mellon University, University of California at Berkeley, University of California at Santa Barbara, University of Illinois at Urbana-Champaign, University of Michigan, and Stanford University.

Artificial Intelligence Lab, Department of MIS, University of Arizona / The NSF/DARPA/NASA Digital Libraries Initiative (DLI) project at the University of Illinois at Urbana-Champaign (UIUC), 1994-1998, had the goal of developing widely usable Web technology to effectively search technical documents on the Internet. The DLI testbed focused on using the document structure to provide federated searches across publisher collections. Our sociology research included the evaluation of its effectiveness under use by over 1,000 UIUC faculty and students, a user community an order of magnitude bigger than the last generation of research projects centered on searching scientific literature. Our technology research developed indexing of the contents of text documents to enable a federated search across multiple sources, testing this on millions of documents for semantic federation. This article will discuss the achievements and difficulties we experienced over the past four years.

There is a serious lack of conceptual clarity in the definitions and uses of learning objects, resulting in design and usability problems in current e-learning systems. The paper proposes ReLOMS, prototype reusable learning objects management system, being implemented to address the problem of usability and reusability of learning objects in e-learning systems.

This conceptual piece presents a framework to aid libraries in gaining a more thorough and holistic understanding of their users and services. Through a presentation of the history of library evaluation, a measurement matrix is developed that demonstrates the relationship between the topics and perspectives of measurement. These measurements are then combined through evaluation criteria, and then different participants in the library system view those criteria for decision-making. By implementing this framework for holistic measurement and cumulative evaluation, library evaluators can gain a more holistic knowledge of the library system and library administrators can be better informed for their decision-making processes.

Artificial Intelligence Lab, Department of MIS, University of Arizona / The National Science Digital Library (NSDL), launched in December 2002, is emerging as a center of innovation in digital libraries as applied to education. As a part of this extensive project, the GetSmart system was created to apply knowledge management techniques in a learning environment. The design of the system is based on an analysis of learning theory and the information search process. Its key notion is the integration of search tools and curriculum support with concept mapping. More than 100 students at the University of Arizona and Virginia Tech used the system in the fall of 2002. A database of more than one thousand student-prepared concept maps has been collected with more than forty thousand relationships expressed in semantic, graphical, node-link representations. Preliminary analysis of the collected data is revealing interesting knowledge representation patterns.

This report describes the results of an Institute of Museum and Library Services (IMLS) funded study to investigate the use of technological or policy tools to control patron access to or use of digital collections of cultural materials created by U.S. archives, libraries and museums. The technological and policy tools serve primarily to control copying or other reuses of digital materials. The study had the following goals: 1. Assess what technical and policy tools cultural institutions are employing to control access to and use of online digital collections. 2. Investigate motivations for controlling access to or use of collections (e.g., copyright, privacy, protecting traditional restrictions, income generation etc.). 3. Investigate discouragers to the implementation of access and use control systems (e.g., preference for open collections, lack of resources, institutional mission, etc.). 4. Gauge interest in implementing technical systems to control access to and use of collections. 5. Determine what types of assistance IMLS could provide. 6. Identify institutions with innovative controlled online collections for follow up case studies on policy, technical and managerial details.

Thesis (Ph. D.)--Drexel University, 1997. / Includes bibliographical references.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Digital libraries with multimedia geographic content present special challenges and opportunities in today's networked information environment. One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, concept-based, geographic information retrieval. Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype that integrates multiple knowledge sources (textual, image, and numerical) to support concept-based geographic information retrieval. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This paper suggests a framework for developing a complete GKRS-based system and describes in detail the prototype system that has been developed so far.