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This practical book uses simple and accessible language to make sense of the many existing and emerging metadata standards, models and approaches.
This book presents a fool-proof method for cleaning and classifying business data. Covering everything from data classification to normalisation, taxonomies and presenting the author's proven COAT methodology, it helps organisations ensure their data is Consistent, Organised, Accurate and Trustworthy. A series of data horror stories outlines what can go wrong in managing data, and if it does, how it can be fixed.
What is metadata and what do I need to know about it? These are two key questions for the information professional operating in the digital age as more and more information resources are available in electronic format. This is a thought-provoking introduction to metadata written by one of its leading advocates. It assesses the current theory and practice of metadata and examines key developments - including global initiatives and multilingual issues - in terms of both policy and technology. Subjects discussed include: What is metadata? definitions and concepts Retrieval environments: web; library catalogues; documents and records management; GIS; e-Learning Using metadata to enhance retrieval: pointing to content; subject retrieval; language control and indexing Information management issues: interoperability; information security; authority control; authentication and legal admissibility of evidence; records management and document lifecyc≤ preservation issues Application of metadata to information management: document and records management; content management systems for the internet Managing metadata: how to develop a schema Standards development: Dublin Core; UK Government metadata standards (eGIF); IFLA FRBR Model for cataloguing resources Looking forward: the semantic web; the Web Ontology Working Group. Readership: This book will be essential reading for network-oriented librarians and information workers in all sectors and for LIS students. In addition, it will provide useful background reading for computer staff supporting information services. Publishers, policy makers and practitioners in other curatorial traditions such as museums work or archiving will also find much of relevance.
This essential new textbook provides cataloguers with the skills needed for transition to Resource Description and Access (RDA). The book builds on John Bowman's highly regarded Essential Cataloguing and gives an introduction to Functional Requirements for Bibliographic Records (FRBR), which provides the conceptual basis for RDA; discusses the differences between AACR2 and RDA; and shows the current state of play in MARC 21. Key topics are: introduction to catalogues and cataloguing standards the FRBRization of the catalogue bibliographic elements access points and headings RDA: the new standard, its development, structure and features AACR and RDA: the similarities and differences between the two standards the MARC21 record bringing it all together the birth of RDA and the death of MARC. The final chapter includes ten records displayed in AACR2 level 1, AACR2 level 2, RDA and MARC 21, making it easy to see the differences at a glance. There is also a fully explained worked example based on RDA Appendix M. Readership: Written at a time of transition in international cataloguing, this book provides cataloguers and students with a background in general cataloguing principles, the current code (AACR2) and format (MARC 21) and the new standard (RDA). The contextual chapters provide library managers with an up-to-date overview of the development of RDA in order to equip them to make the transition. The book will be essential reading for students of library and information studies and practising library and information professionals in all sectors. It will also be of great interest to the archives sector.
Facet Analysis provides a general overview of facet analysis as a formal methodology for building knowledge organization and search tools and as a general knowledge organization theory.
This book constitutes the thoroughly refereed proceedings of the 11th International Conference on Metadata and Semantic Research, MTSR 2017 2017, held in Tallinn, Estonia, November 28th to December 1st, 2017. The 18 full and 13 short papers presented were carefully reviewed and selected from 58 submissions. They focus on the Internet of Things (IoT) and the practical implementation of ontologies and linked data. Further topics are theoretical and foundational principles of metadata; ontologies and information organization; applications of linked data, open data, big data and user-generated metadata; digital interconnectedness; metadata standardization; authority control and interoperability in digital libraries and research data repositories; emerging issues in RDF, OWL, SKOS, schema.org, BIBFRAME, metadata and ontology design; linked data applications for e-books; digital publishing and Content Management Systems (CMSs); content discovery services, search, information retrieval and data visualization applications.
This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions.
Information retrieval (IR) is a complex human activity supported by sophisticated systems. Information science has contributed much to the design and evaluation of previous generations of IR system development and to our general understanding of how such systems should be designed and yet, due to the increasing success and diversity of IR systems, many recent textbooks concentrate on IR systems themselves and ignore the human side of searching for information. This book is the first text to provide an information science perspective on IR. Unique in its scope, the book covers the whole spectrum of information retrieval, including: history and background information behaviour and seeking task-based information searching and retrieval approaches to investigating information interaction and behaviour information representation access models evaluation interfaces for IR interactive techniques web retrieval, ranking and personalization recommendation, collaboration and social search multimedia: interfaces and access. Readership: Senior undergraduates and masters' level students of all information and library studies courses and practising LIS professionals who need to better appreciate how IR systems are designed, implemented and evaluated.
This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.
Since he began posting in 2003, Dempsey has used his blog to explore nearly every important facet of library technology, from the emergence of Web 2.0 as a concept to open source ILS tools and the push to web-scale library management systems.