Search (503 results, page 26 of 26)

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Abstract

This book shows you how to harness the power of linked data and web-scale discovery systems to manage and link widely varied content across your library collection. Libraries are increasingly using web-scale discovery systems to help clients find a wide assortment of library materials, including books, journal articles, special collections, archival collections, videos, music and open access collections. Depending on the library material catalogued, the discovery system might need to negotiate different metadata standards, such as AACR, RDA, RAD, FOAF, VRA Core, METS, MODS, RDF and more. In Managing Metadata in Web-Scale Discovery Systems, editor Louise Spiteri and a range of international experts show you how to: * maximize the effectiveness of web-scale discovery systems * provide a smooth and seamless discovery experience to your users * help users conduct searches that yield relevant results * manage the sheer volume of items to which you can provide access, so your users can actually find what they need * maintain shared records that reflect the needs, languages, and identities of culturally and ethnically varied communities * manage metadata both within, across, and outside, library discovery tools by converting your library metadata to linked open data that all systems can access * manage user generated metadata from external services such as Goodreads and LibraryThing * mine user generated metadata to better serve your users in areas such as collection development or readers' advisory. The book will be essential reading for cataloguers, technical services and systems librarians and library and information science students studying modules on metadata, cataloguing, systems design, data management, and digital libraries. The book will also be of interest to those managing metadata in archives, museums and other cultural heritage institutions.

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Footnote

What is, after all the FRBR model? The question is asked in the subtitle itself: is it a "hype or cureall?" It certainly is the talk of the day in libraries and similar institutions, a very popular topic for professional meetings, a challenging task for system vendors and food for thought for scholars both in terminology and in content. As for the solutions it offers, they enable simplified and more structured catalogues of large collections and perhaps easier ways to cataloguing resources of many different types. Once implemented in catalogues, the benefits will be both on the librarian's side and on the end user's side. According to Patrick LeBoeuf the model is a beginning and there are two directions for its development as far as the authors of the articles imply: the first, oriented to the configuration of FRANAR or FRAR, the second, oriented to what has already been established and defined as FRSAR (Functional Requirements for Subject Authority Records). The latter is meant to build a conceptual model for Group 3 entities within the FRBR framework related to the aboutness of the work and assist in an assessment of the potential for international sharing and use of subject authority data both within the library sector and beyond. A third direction, not present in the work considered, yet mentioned by the editor, is oriented towards the development of "the CIDOC CRM semantic model for cultural heritage information in museums and assimilated institutions" (p. 6). By merging the FRBR working group with the CIDOC CRM Special Interest Group a FRBR/CRM Harmonization Group has been created its scope being the "translation" of FRBR into object-oriented formalism. The work under review is the expected and welcome completion of the FRBR Final Report of 1998, addressing librarians, library science teaching staff, students, and library system vendors, a comprehensive source of information on theoretical aspects and practical application of the FRBR conceptual model. A good companion clarifying many FRBR issues the collection is remarkably well structured and offers a step-by-step insight into the model. An additional feature of the work is the very helpful index at the back of the book providing an easy access to the main topics discussed."

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Footnote

The book does achieve its aim of being a starting point for someone interested in the state of some areas of AI research at the beginning of the new millennium. The book's most irritating feature is the different writing styles of the authors. The book is organized as a collection of papers similar to a typical graduate survey course packet, and as a result the book does not possess a narrative flow. Also the book contains a number of other major weaknesses such as a lack of an introductory or concluding chapter. The book could greatly benefit from an introductory chapter that would introduce readers to the areas of AI, explain why such a book is needed, and explain why each author's research is important. The manner in which the book currently handles these issues is a preface that talks about some of the above issues in a superficial manner. Also such an introductory chapter could be used to expound an what level of AI mathematical and statistical knowledge is expected from readers in order to gain maximum benefit from this book. A concluding chapter would be useful to readers interested in the other areas of AI not covered by the book, as well as open issues common to all of the research presented. In addition, most of the contributors come exclusively from the computer science field, which heavily slants the work toward the computer science community. A great deal of the research presented is being used by a number of research communities outside of computer science, such as biotechnology and information technology. A wider audience for this book could have been achieved by including a more diverse range of authors showing the interdisciplinary nature of many of these fields. Also the book's editors state, "The reader is expected to have basic knowledge of AI at the level of an introductory course to the field" (p vii), which is not the case for this book. Readers need at least a strong familiarity with many of the core concepts within AI, because a number of the chapters are shallow and terse in their historical overviews. Overall, this book would be a useful tool for a professor putting together a survey course an AI research. Most importantly the book would be useful for eager graduate students in need of a starting point for their research for their thesis. This book is best suited as a reference guide to be used by individuals with a strong familiarity with AI."