Access to educational material has become an important issue for many stakeholders and the focus of many projects worldwide. Resource discovery in many educational gateways is usually based on metadata and this is the area of many important developments. Resource metadata has a central role in the management of educational material and as a result there are several important metadata standards in use in the educational domain. One of the most widely used general metadata standards for learning material is the Dublin Core Metadata Element Set. The application of this general purpose, metadata standard for complex and heterogeneous educational material is not straightforward. This paper will give an overview of some practical issues and necessary steps in deploying Dublin Core based on the LITC experience in EASEL (Educators Access to Services in the Electronic Landscape)project.

Artificial Intelligence Lab, Department of MIS, University of Arizona / The rapid proliferation of textual and multimedia online databases, digital libraries, Internet servers, and intranet services has turned researchers' and practitioners' dream of creating an information-rich society into a nightmare of info-gluts. Many researchers believe that turning an info-glut into a useful digital library requires automated techniques for organizing and categorizing large-scale information. This paper presents research in which we sought to develop a scaleable textual classification and categorization system based on the Kohonen's self-organizing feature map (SOM) algorithm. In our paper, we show how self-organization can be used for automatic thesaurus generation. Our proposed data structure and algorithm took advantage of the sparsity of coordinates in the document input vectors and reduced the SOM computational complexity by several order of magnitude. The proposed Scaleable SOM (SSOM) algorithm makes large-scale textual categorization tasks a possibility. Algorithmic intuition and the mathematical foundation of our research are presented in detail. We also describe three benchmarking experiments to examine the algorithm's performance at various scales: classification of electronic meeting comments, Internet homepages, and the Compendex collection.

The marginalization of people through classification schemes results in inadequate access to information about these people when the context is, for example, a bibliographic classification system. When the context is the classification of the people themselves, they themselves are underrepresented, for instance, by society and government support. Taking the case of the natural disaster survivor, this paper explores appropriate steps to devising an accurate classification scheme of the survivors.

In this paper, we show how Semantic Web techniques can help to solve semantic interoperability issues in the cultural heritage domain. In particular, these techniques can enable integrated access to heterogeneous collections by representing their controlled description vocabularies (e.g. thesauri) in a standardized format â Simple Knowledge Organization System (SKOS). We also present existing automatic alignment procedures that can assist cultural heritage practitioners to connect such vocabularies at the semantic level, building similarity links between the concepts they contain.

James Duff Brown (1862-1914), an important figure in librarianship in late nineteenth and early twentieth century England, made contributions in many areas of his chosen field. His Subject Classification (SC), however, has not received much recognition for its theoretical and practical contributions to bibliographic classification theory and practice in the twentieth century. This paper discusses some of the elements of SC that both did and did not inform future bibliographic classification work, considers some contrasting evaluation methods in the light of advances in bibliographic classification theory and practice and of commentaries on SC, and suggests directions for further research.

While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...

INTRODUCTION Medical professionals seek to capture papers which can be located via keyword or free text search in digital libraries or on the web but are also interested in finding material that has not yet been indexed in on-line databases. Search engines provide a multitude of results [1]. Social bookmarking, where users tag items for their own use, offers a way to locate new and relevant information. CiteULike (citeulike.org), a social bookmarking service, allows articles to be tagged with useful keywords for later retrieval. RELATED STUDIES A previous study [2] compared social bookmarking to existing information organisation structures and found similarities in terminology use and intriguing differences. A sample of articles tagged on CiteULike was examined for contextual differences in keyword usage between users of social bookmarking sites, authors and indexers. Many tags were related to thesaurus terms (descriptors), but were not formally in the thesaurus. [2] This study examines how term usage patterns in tags, keywords and descriptors suggest a similar (or differing) context between users, authors and intermediaries. METHODOLOGY This study examines the use of tags on CiteULike from three medical or biology journals (JAMA, Proteins, and Journal of Molecular Biology) indexed in Pubmed. 1299 unique articles were retrieved from Citeulike; Medical Subject Headings (MeSH) were collected from Pubmed. Articles were analysed using standard informetric techniques to examine the use of user assigned tags and their Pubmed assigned MeSH index terms. Data was analysed for term usage and categorised to see what contextual clues users expose in their tag use. RESULTS Articles were tagged by up to 14 users (average 2-4). 1449 unique tags were used in the data set. Some articles were heavily tagged by users (max. 29, min. 1, median 2). Descriptors were more heavily assigned to articles (2746 unique descriptors). Articles had, on average, 10 descriptors assigned (max. 40, min. 2). Some tags occurred frequently: protein_structure (140), no-tag (134), and protein (114). By journal, tags were: docking (Proteins, 85), no-tag (JAMA, 20), and protein_structure (J Mol Biol, 52). No-tag (system assigned) indicated no tag assigned. Descriptors were more heavily reused than tags, for example: 'Models, Molecular' (550), Protein Conformation (363), and Humans (341). By journal, descriptors were: 'Models, Molecular' (Proteins, 252), 'Models, Molecular' (J Mol Biol, 235), and Humans (JAMA, 137). DISCUSSIONS AND CONCLUSIONS Comparison of tag and descriptor lists shows many of the same similarities and differences as the previous study [2]. Many user terms were related to the author and intermediary terms but not in the thesaurus (e.g. 'diet' and 'fat' used separately in the tag lists where they were linked as 'dietary fats' in the thesaurus). Terms such as 'human' and 'family-studies' show users tagging biology articles are interested in methodology and user groups associated with articles. This study has system design implications for accessing, indexing and searching document spaces. Users express frustration trying to narrow search results. Controlled vocabularies help narrow a search to a manageable size but can be expensive. User tagging could provide additional access points to traditional controlled vocabularies and the associative classifications necessary to tie documents and articles to time and task relationships among other novel items. REFERENCES [1] Tang H, Ng J.HK. 2006. Googling for a diagnosis -- use of Google as a diagnostic aid: internet based study. BMJ 333 (2 Dec), 1143-1145. [2] Kipp MEI. 2006. Complementary or discrete contexts in online indexing: A comparison of user, creator, and intermediary keywords. Canadian Journal of Information and Library Science (in press) http://dlist.sir.arizona.edu/1533/

Geospatial information technologies revolutionize the way we have traditionally approached navigation and browsing in information systems. Colorful graphics, statistical summaries, geospatial relationships of underlying collections make them attractive for text retrieval systems. This paper examines the nature of georeferenced information in academic library catalogs organized according to the Library of Congress Classification (LCC) with the goal of understanding their implications for geovisualization of library collections.

This is a preliminary digitization of S.R. Ranganathan's Prolegomena to Library Classification (Assisted by M.A. Gopinath). Published by Asia Publishing House (New York), 1967 (printed in India). Copyright permissions granted from the copyright holder: Sarada Ranganathan Endowment for Library Science (SRELS). To purchase reprints of this work, please visit Ess Ess Publications at http://www.essessreference.com/. Table of Contents: Part A: Introduction includes Preface to Edition 1 by Sayers, Genesis of Edition 1 (1937), Development of Edition 2 (1957), Development of Edition 3 (1967), Features of Edition 3 (1967); Part B: Summary of Normative Principles; Part C: Basic Concepts and Terminology of Classification; Part D: Normative Principles; Part E: Canons for Work in the Idea Plane; Part F: Principles for Helpful Sequence; Part G: Canons for Work in the Verbal Plane; Part H: Notational Plane; Part J: Canons for Work in the Notational Plane; Part K: Canons for Mnemonics; Part I: Notational System for a Growing Universe; Part M: Planes of Work; Part N: Foci in an Array; Part P: Formation, Structure, and Development of Subjects; Part Q: Classification as Transformation; Part R: Analytico-Synthetic Classification (Idea Plane); Part S: Analytico-Synthetic Classification (Notational Plane); Part T: Quasi-Subject and Subject Bundle; Part U: Book Number; Part V: Use of Collection Number; Part W: Universal & Special Classification; Part X: Reflections; Bibliographical References; Index.

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