15 research outputs found

    Cataloging Expert Systems: Optimism and Frustrated Reality

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    There is little question that computers have profoundly changed how information professionals work. The process of cataloging and classifying library materials was one of the first activities transformed by information technology. The introduction of the MARC format in the 1960s and the creation of national bibliographic utilities in the 1970s had a lasting impact on cataloging. In the 1980s, the affordability of microcomputers made the computer accessible for cataloging, even to small libraries. This trend toward automating library processes with computers parallels a broader societal interest in the use of computers to organize and store information. Following World War II, military personnel and scientists began to experiment with computers in all areas of their work, giving birth to computer science. As this field advanced, researchers began to wonder if computers might be programmed to simulate human intelligence. If so, the benefits could be extraordinary. These attempts to impart human reasoning and thought to computer software formed the basis for artificial intelligence (AI) studies, and dovetailed nicely with a growing interest in cognitive psychology. Artificial intelligence research today focuses on several areas, including natural language processing, computer learning, computer vision, problem solving, and expert systems. It is the last of these that has received the most attention in librarianship in the last two decades. Expert systems were proposed and created for reference service, acquisitions, vendor management, and cataloging. Unfortunately, Sauperl and Saye3 show that the development of cataloging expert systems has practically ceased. This frenzy of publication about expert systems, followed by a rather sudden decline, warrants investigation

    Mobile School Health Information Initiative (MoSHI)

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    The Mobile School Health Information Initiative: creating and sustaining a free curriculum for P-12 staff to find credible health information

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    Three health sciences librarians created a curriculum to connect pre-school – grade 12 (P-12) personnel with credible health information. The course focuses on MedlinePlus® and KidsHealth.org®. They obtained external funding to deliver a revised curriculum for free throughout the metropolitan area. The funded portion of the project reached 93 people at 8 sites. Efforts to sustain the program beyond its funded cycle have reached another 33 people. Evaluations indicate the curriculum successfully equips staff to be health information champions within their schools. Participants report increased confidence locating credible health information. Written comments indicate both short-term gains and sustained use of the knowledge

    Cataloging Expert Systems: Optimism and Frustrated Reality

    Get PDF
    There is little question that computers have profoundly changed how information professionals work. The process of cataloging and classifying library materials was one of the first activities transformed by information technology. The introduction of the MARC format in the 1960s and the creation of national bibliographic utilities in the 1970s had a lasting impact on cataloging. In the 1980s, the affordability of microcomputers made the computer accessible for cataloging, even to small libraries. This trend toward automating library processes with computers parallels a broader societal interest in the use of computers to organize and store information. Following World War II, military personnel and scientists began to experiment with computers in all areas of their work, giving birth to computer science. As this field advanced, researchers began to wonder if computers might be programmed to simulate human intelligence. If so, the benefits could be extraordinary. These attempts to impart human reasoning and thought to computer software formed the basis for artificial intelligence (AI) studies, and dovetailed nicely with a growing interest in cognitive psychology. Artificial intelligence research today focuses on several areas, including natural language processing, computer learning, computer vision, problem solving, and expert systems. It is the last of these that has received the most attention in librarianship in the last two decades. Expert systems were proposed and created for reference service, acquisitions, vendor management, and cataloging. Unfortunately, Sauperl and Saye3 show that the development of cataloging expert systems has practically ceased. This frenzy of publication about expert systems, followed by a rather sudden decline, warrants investigation
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