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LCSH

Machine / readable bibliographic data
Subject cataloging / Data processing
Online bibliographic searching
Indexing / Data processing

Subject

Machine / readable bibliographic data
Subject cataloging / Data processing
Online bibliographic searching
Indexing / Data processing

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Footnote

Rez. in: Philosophisch-ethische Rezensionen vom 09.11.2019 (Jürgen Czogalla), Unter: https://philosophisch-ethische-rezensionen.de/rezension/Goedert1.html. In: B.I.T. online 23(2020) H.3, S.345-347 (W. Sühl-Strohmenger) [Unter: https%3A%2F%2Fwww.b-i-t-online.de%2Fheft%2F2020-03-rezensionen.pdf&usg=AOvVaw0iY3f_zNcvEjeZ6inHVnOK]. In: Open Password Nr. 805 vom 14.08.2020 (H.-C. Hobohm) [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzE0MywiOGI3NjZkZmNkZjQ1IiwwLDAsMTMxLDFd].

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LCSH

Subject cataloguing / Data processing
Machine / readable bibliographic data

Subject

Subject cataloguing / Data processing
Machine / readable bibliographic data

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Abstract

MARC is an acronym for Machine Readable Catalogue or Cataloguing. This general description, howcver, is rather misleading as MARC is neither a kind of catalogue nor a method of cataloguing. In fact, MARC is a Standardformat for representing bibliographic information for handling by computer. While the MARC format was primarily designed to serve the needs of libraries, the concept has since been embraced by the wider information community as a convenient way of storing and exchanging bibliographic data. The original MARC format was developed at the Library of Congress in 1965-6 leading to a pilot project, known as MARC I, which had the aim of investigating the feasibility of producing machine-readable catalogue data. Similar work was in progress in the United Kingdom whcre the Council of the British National Bibliography had set up the BNB MARC Project with the rennt of examining the use of machine-readable data in producing the printed British National Bibliography (BNB). These parallel developments led to Anglo-American co-operation an the MARC 11 project which was initiated in 1968. MARC II was to prove instrumental in defining the concept of MARC as a communications format.

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Abstract

Describes a project based at the ESRC Data Archive, Esses University to examine standards for cataloguing computer files and the feasibility of creating a union catalogue of computer files. A pilot scheme was set up to enable the MARC record output of the ESRC Data Archive to be merged with the software records of the NISS (National Information on Software and Services) data base, which is available on the JANET network.

LCSH

Cataloging of machine / readable data files

Subject

Cataloging of machine / readable data files

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Abstract

New technologies will underpin the future generation of library catalogues. To facilitate their role providing information, serving users, and fulfilling their mission as cultural heritage and memory institutions, libraries must take a technological leap; their standards and services must be transformed to those of the Semantic Web. Bibliographic Information Organization in the Semantic Web explores the technologies that may power future library catalogues, and argues the necessity of such a leap. The text introduces international bibliographic standards and models, and fundamental concepts in their representation in the context of the Semantic Web. Subsequent chapters cover bibliographic information organization, linked open data, methodologies for publishing library metadata, discussion of the wider environment (museum, archival and publishing communities) and users, followed by a conclusion.

LCSH

Machine / readable bibliographic data

RSWK

Bibliografische Daten / Informationsmanagement / Semantic Web / Functional Requirements for Bibliographic Records
Bibliografische Daten / Semantic Web / Metadaten / Linked Data

Subject

Bibliografische Daten / Informationsmanagement / Semantic Web / Functional Requirements for Bibliographic Records
Bibliografische Daten / Semantic Web / Metadaten / Linked Data
Machine / readable bibliographic data

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Footnote

Vgl. auch unter: http://lcweb.loc.gov/marc/umb/. - Understanding MARC: Bibliographic was a copyrighted work originally published by the Follett Software Co. in 1988 (second edition, 1989, third edition, 1990, fourth edition, 1994, fifth edition, 1998)

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LCSH

Machine / readable bibliographic data
Subject cataloging / Data processing
Online bibliographic searching

Subject

Machine / readable bibliographic data
Subject cataloging / Data processing
Online bibliographic searching

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Subject cataloging / Germany / Data processing / Congresses
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Subject cataloging / Germany / Data processing / Congresses
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Content

Inhalt: Chapters 2 to 5: Scopes, Domains, and Display Media (pp. 47-102) Chapters 6 to 8: Documents, Analysis, and Indexing (pp. 103-176) Chapters 9 to 10: Exhaustivity and Specificity (pp. 177-196) Chapters 11 to 13: Displayed/Nondisplayed Indexes, Syntax, and Vocabulary Management (pp. 197-364) Chapters 14 to 16: Surrogation, Locators, and Surrogate Displays (pp. 365-390) Chapters 17 and 18: Arrangement and Size of Displayed Indexes (pp. 391-446) Chapters 19 to 21: Search Interface, Record Format, and Full-Text Display (pp. 447-536) Chapter 22: Implementation and Evaluation (pp. 537-541)

Footnote

Rez. in JASIST 57(2006) no.10, S.1412-1413 (R. W. White): "Information Retrieval Design is a textbook that aims to foster the intelligent user-centered design of databases for Information Retrieval (IR). The book outlines a comprehensive set of 20 factors. chosen based on prior research and the authors' experiences. that need to he considered during the design process. The authors provide designers with information on those factors to help optimize decision making. The book does not cover user-needs assessment, implementation of IR databases, or retries al systems, testing. or evaluation. Most textbooks in IR do not offer a substantive walkthrough of the design factors that need to be considered Mien des eloping IR databases. Instead. they focus on issues such as the implementation of data structures, the explanation of search algorithms, and the role of human-machine interaction in the search process. The book touches on all three, but its focus is on designing databases that can be searched effectively. not the tools to search them. This is an important distinction: despite its title. this book does not describe how to build retrieval systems. Professor Anderson utilizes his wealth of experience in cataloging and classification to bring a unique perspective on IR database design that may be useful for novices. for developers seeking to make sense of the design process, and for students as a text to supplement classroom tuition. The foreword and preface. by Jessica Milstead and James Anderson. respectively, are engaging and worthwhile reading. It is astounding that it has taken some 20 years for anyone to continue the stork of Milstead and write as extensively as Anderson does about such an important issue as IR database design. The remainder of the book is divided into two parts: Introduction and Background Issues and Design Decisions. Part 1 is a reasonable introduction and includes a glossary of the terminology that authors use in the book. It is very helpful to have these definitions early on. but the subject descriptors in the right margin are distracting and do not serve their purpose as access points to the text. The terminology is useful to have. as the authors definitions of concepts do not lit exactly with what is traditionally accepted in IR. For example. they use the term 'message' to icier to what would normally be called .'document" or "information object." and do not do a good job at distinguishing between "messages" and "documentary units". Part 2 describes components and attributes of 1R databases to help designers make design choices. The book provides them with information about the potential ramifications of their decisions and advocates a user-oriented approach to making them. Chapters are arranged in a seemingly sensible order based around these factors. and the authors remind us of the importance of integrating them. The authors are skilled at selecting the important factors in the development of seemingly complex entities, such as IR databases: how es er. the integration of these factors. or the interaction between them. is not handled as well as perhaps should be. Factors are presented in the order in which the authors feel then should be addressed. but there is no chapter describing how the factors interact. The authors miss an opportunity at the beginning of Part 2 where they could illustrate using a figure the interactions between the 20 factors they list in a way that is not possible with the linear structure of the book.

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Abstract

The Bayerische Staatsbibliothek acting on behalf of the Consortium of European Research Libraries (CERL) was responsible for the preparation of this report under a contract agreed with the Commission of the European Communities Directorate General XIII as part of their Libraries Programme. The report considers the feasibility of the application of UNIMARC to multinational databases, and was based on a comparison of machine-readable bibliographic records in the UNIMARC format from 6 different national sources. Some are conversions from other formats, while others are 'native' UNIMARC records. The records are of books of the hand press period, that is, from the time of Gutenberg to about 1830

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Abstract

Indexing and abstracting are not activities that should be looked upon as ends in themselves. It is the results of these activities that should be evaluated and this can only be done within the context of a particular database, whether in printed or machine-readable form. In this context, the indexing can be judged successful if it allows searchers to locate items they want without having to look at many they do not want. This book intended primarily as a text to be used in teaching indexing and abstracting of Library and information science. It is an immense value to all individuals and institutions involved in information retrieval and related activities, including librarians, managers of information centres and database producers.

Content

Inhalt: 1. Indexing and Abstracting 2. Automatic Indexing and Automatic Abstracting 3. Principles of Indexing 4.Periodicals Listing and Accessioning 5. Online Computer Service 6. Dialog, Searching and Bibliographic Display 7. Books 8. Bibliographic Control 9. Abstracting Functions 10. Acquisition System 11. Future of Indexing and Abstracting Services

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Content

Enthält u.a.: Grimaldi, T.: The object of cataloguing; Byrum, J.D., O.M.A. Madison: Reflections an the goals, concepts and recommendations of the IFLA study an Functional Requirements of Bibliographic Records;

Date

29. 8.2005 12:54:22

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Content

What is metadata? - Metadata schemas & their relationships to particular communities - Library and information-related metadata schemas - Creating library metadata for monographic materials - Creating library metadata for continuing materials - Integrating library metadata into local cataloging and bibliographic - databases - Digital collections/digital libraries - Archiving & preserving digital materials - Impact of digital resources on library services - Future possibilities

Footnote

Rez. in: JASIST. 58(2007) no.6., S.909-910 (A.D. Petrou): "A division in metadata definitions for physical objects vs. those for digital resources offered in Chapter 1 is punctuated by the use of broader, more inclusive metadata definitions, such as data about data as well as with the inclusion of more specific metadata definitions intended for networked resources. Intertwined with the book's subject matter, which is to "distinguish traditional cataloguing from metadata activity" (5), the authors' chosen metadata definition is also detailed on page 5 as follows: Thus while granting the validity of the inclusive definition, we concentrate primarily on metadata as it is most commonly thought of both inside and outside of the library community, as "structured information used to find, access, use and manage information resources primarily in a digital environment." (International Encyclopedia of Information and Library Science, 2003) Metadata principles discussed by the authors include modularity, extensibility, refinement and multilingualism. The latter set is followed by seven misconceptions about metadata. Two types of metadata discussed are automatically generated indexes and manually created records. In terms of categories of metadata, the authors present three sets of them as follows: descriptive, structural, and administrative metadata. Chapter 2 focuses on metadata for communities of practice, and is a prelude to content in Chapter 3 where metadata applications, use, and development are presented from the perspective of libraries. Chapter 2 discusses the emergence and impact of metadata on organization and access of online resources from the perspective of communities for which such standards exist and for the need for mapping one standard to another. Discussion focuses on metalanguages, such as Standard Generalized Markup Language (SGML) and eXtensible Markup Language (XML), "capable of embedding descriptive elements within the document markup itself' (25). This discussion falls under syntactic interoperability. For semantic interoperability, HTML and other mark-up languages, such as Text Encoding Initiative (TEI) and Computer Interchange of Museum Information (CIMI), are covered. For structural interoperability, Dublin Core's 15 metadata elements are grouped into three areas: content (title, subject, description, type, source, relation, and coverage), intellectual property (creator, publisher, contributor and rights), and instantiation (date, format, identifier, and language) for discussion.

LCSH

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PRECIS

Documents / Cataloguing / Machine / readable files / International exchange / Formats: UNIMARC / Manuals

Subject

Documents / Cataloguing / Machine / readable files / International exchange / Formats: UNIMARC / Manuals

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Abstract

Using subject headings for Online Retrieval is an indispensable tool for online system desingners who are developing new systems or refining exicting ones. The book describes subject analysis and subject searching in online catalogs, including the limitations of retrieval, and demonstrates how such limitations can be overcome through system design and programming. The book describes the Library of Congress Subject headings system and system characteristics, shows how information is stored in machine readable files, and offers examples of and recommendations for successful methods. Tables are included to support these recommendations, and diagrams, graphs, and bar charts are used to provide results of data analyses.

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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

LCSH

Data mining

RSWK

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)

Series

Morgan Kaufmann series in data management systems

Subject

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)
Data mining

Theme

Data Mining