Thesis (Ph. D.)--Rutgers University, 1964. / eContent provider-neutral record in process. Description based on print version record. Bibliography: leaves 105-137.

Much work in knowledge organization (KO) is conceptual, which results in a theoretical framework that is itself largely conceptual. In some cases empirical methods have been employed as well for direct observation of phenomena. Direct observation provides a critical base point and a variety of empirical approaches have been used to good effect in KO. The phenomenon of instantiation has been examined to date almost entirely based on the analysis of data derived from empirical analysis. In the present paper we demonstrate the efficacy of the empirical model for category generation by taking one category of instantiationâ the performance workâ and submitting it to analytical scrutiny. Data from three analytical studies are reviewed and placed alongside evidence from datasets gathered for prior studies on instantiation. A performance work is realized in space and time, and thus exists spatiotemporally. The performance work might be derived from a precedent work, related to other works that are embedded, have adjunct documentation, and be accompanied by antecedent works. A naïve classification is derived empirically, a model follows rationally, and together with semiotic elements a partial typology is generated that represents the essential knowledge elements from which a KO schema for performance works might evolve.

This is a presentation of the library's most enduring artifact: the bibliographic record. The focus is on understanding the theory behind IFLA's Functional Requirements for Bibliographic Records (FRBR). Illustrations, practical implementations, and research initiatives are also summarized. A deeper understanding of the importance of "works" and the legacy that it brings along are the goal of this entertaining and informative look into our past, present and future.

No description available.

References and resources (most from the Internet) is support of graduate instruction in the area of Organization of Information.

The teaching of authority control in schools of library and information science is alive and well, even though it is not perceived this way by some former students. Many professors are fervently attempting to imbue the next generation of librarians with an understanding of the necessity for authority control. Unfortunately, they have to fight the nonunderstanding of colleagues, the lack of course time to be as thorough as desired, and the perception that information technology is uppermost in importance among courses to be taught. However, because the chaotic environment of the Web has brought attention to the need for authority control (e.g., the "semantic web"), we have a new opportunity to teach these concepts to a new generation of information professionals.

This lists references and resources (mostly on the Internet) that are used in support of graduate instruction in the area of Organization of Information.

This paper examines important artifacts of scientific research, namely models. It proposes that the representations of scientific models be treated as works. It discusses how bibliographic families of models may better reflect disciplinary intellectual structures and relationships, thereby providing information retrieval that is reflective of human information seeking and use purposes such as teaching and learning. Two examples of scientific models are presented using the Dublin Core metadata elements.

The presentation discusses the 1) purpose of inquiry into works, 2) an historical perspective, 3) user research, and 4) research possibilities.

This 19 slide presentation at ASIS&T Annual Meeting 2003, Long Beach, California discusses how scientific models may be considered as "works" for information retrieval purposes. Bibliographic relationships are used to determine the physical components (the ideational content as instantiations) and faceted conceptual relationships to identify the semantic content of scientific models. Water Quality models with progenitors such as Street and Phelps are briefly discussed. Future research directions include examining the boundaries of models and investigating displays for scientific model learning and use.