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Abstract

This book provides a practical introduction to metadata for the digital library, describing in detail how to implement a strategic approach which will enable complex digital objects to be discovered, delivered and preserved in the short- and long-term.
The range of metadata needed to run a digital library and preserve its collections in the long term is much more extensive and complicated than anything in its traditional counterpart. It includes the same 'descriptive' information which guides users to the resources they require but must supplement this with comprehensive 'administrative' metadata: this encompasses technical details of the files that make up its collections, the documentation of complex intellectual property rights and the extensive set needed to support its preservation in the long-term. To accommodate all of this requires the use of multiple metadata standards, all of which have to be brought together into a single integrated whole.
Metadata in the Digital Library is a complete guide to building a digital library metadata strategy from scratch, using established metadata standards bound together by the markup language XML. The book introduces the reader to the theory of metadata and shows how it can be applied in practice. It lays out the basic principles that should underlie any metadata strategy, including its relation to such fundamentals as the digital curation lifecycle, and demonstrates how they should be put into effect. It introduces the XML language and the key standards for each type of metadata, including Dublin Core and MODS for descriptive metadata and PREMIS for its administrative and preservation counterpart. Finally, the book shows how these can all be integrated using the packaging standard METS. Two case studies from the Warburg Institute in London show how the strategy can be implemented in a working environment. The strategy laid out in this book will ensure that a digital library's metadata will support all of its operations, be fully interoperable with others and enable its long-term preservation. It assumes no prior knowledge of metadata, XML or any of the standards that it covers. It provides both an introduction to best practices in digital library metadata and a manual for their practical implementation.

Content

Inhalt: 1 Introduction, Aims and Definitions -- 1.1 Origins -- 1.2 From information science to libraries -- 1.3 The central place of metadata -- 1.4 The book in outline -- 2 Metadata Basics -- 2.1 Introduction -- 2.2 Three types of metadata -- 2.2.1 Descriptive metadata -- 2.2.2 Administrative metadata -- 2.2.3 Structural metadata -- 2.3 The core components of metadata -- 2.3.1 Syntax -- 2.3.2 Semantics -- 2.3.3 Content rules -- 2.4 Metadata standards -- 2.5 Conclusion -- 3 Planning a Metadata Strategy: Basic Principles -- 3.1 Introduction -- 3.2 Principle 1: Support all stages of the digital curation lifecycle -- 3.3 Principle 2: Support the long-term preservation of the digital object -- 3.4 Principle 3: Ensure interoperability -- 3.5 Principle 4: Control metadata content wherever possible -- 3.6 Principle 5: Ensure software independence -- 3.7 Principle 6: Impose a logical system of identifiers -- 3.8 Principle 7: Use standards whenever possible -- 3.9 Principle 8: Ensure the integrity of the metadata itself -- 3.10 Summary: the basic principles of a metadata strategy -- 4 Planning a Metadata Strategy: Applying the Basic Principles -- 4.1 Introduction -- 4.2 Initial steps: standards as a foundation -- 4.2.1 'Off-the shelf' standards -- 4.2.2 Mapping out an architecture and serialising it into a standard -- 4.2.3 Devising a local metadata scheme -- 4.2.4 How standards support the basic principles -- 4.3 Identifiers: everything in its place -- 5 XML: The Syntactical Foundation of Metadata -- 5.1 Introduction -- 5.2 What XML looks like -- 5.3 XML schemas -- 5.4 Namespaces -- 5.5 Creating and editing XML -- 5.6 Transforming XML -- 5.7 Why use XML? -- 6 METS: The Metadata Package -- 6.1 Introduction -- 6.2 Why use METS?.

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Abstract

"Big Data" is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six "provocations" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

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Abstract

For decades, we have been told we live in the "information age"-a time when disruptive technological advancement has reshaped the categories and social uses of knowledge and when quantitative assessment is increasingly privileged. Such methodologies and concepts of information are usually considered the provenance of the natural and social sciences, which present them as politically and philosophically neutral. Yet the humanities should and do play an important role in interpreting and critiquing the historical, cultural, and conceptual nature of information. This book is one of two companion volumes that explore theories and histories of information from a humanistic perspective. They consider information as a long-standing feature of social, cultural, and conceptual management, a matter of social practice, and a fundamental challenge for the humanities today. Information: A Reader provides an introduction to the concept of information in historical, literary, and cultural studies. It features excerpts from more than forty texts by theorists and critics who have helped establish the notion of the "information age" or expand upon it. The reader establishes a canonical framework for thinking about information in humanistic terms. Together with Information: Keywords, it sets forth a major humanistic vision of the concept of information.

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Abstract

For decades, we have been told we live in the "information age"-a time when disruptive technological advancement has reshaped the categories and social uses of knowledge and when quantitative assessment is increasingly privileged. Such methodologies and concepts of information are usually considered the provenance of the natural and social sciences, which present them as politically and philosophically neutral. Yet the humanities should and do play an important role in interpreting and critiquing the historical, cultural, and conceptual nature of information. This book is one of two companion volumes that explore theories and histories of information from a humanistic perspective. They consider information as a long-standing feature of social, cultural, and conceptual management, a matter of social practice, and a fundamental challenge for the humanities today. Bringing together essays by prominent critics, Information: Keywords highlights the humanistic nature of information practices and concepts by thinking through key terms. It describes and anticipates directions for how the humanities can contribute to our understanding of information from a range of theoretical, historical, and global perspectives. Together with Information: A Reader, it sets forth a major humanistic vision of the concept of information.

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Date

22. 6.2008 13:03:30

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Content

Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together

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Abstract

An argument that information exists at different levels of analysis-syntactic, semantic, and pragmatic-and an exploration of the implications. Although this is the Information Age, there is no universal agreement about what information really is. Different disciplines view information differently; engineers, computer scientists, economists, linguists, and philosophers all take varying and apparently disconnected approaches. In this book, Antonio Badia distinguishes four levels of analysis brought to bear on information: syntactic, semantic, pragmatic, and network-based. Badia explains each of these theoretical approaches in turn, discussing, among other topics, theories of Claude Shannon and Andrey Kolomogorov, Fred Dretske's description of information flow, and ideas on receiver impact and informational interactions. Badia argues that all these theories describe the same phenomena from different perspectives, each one narrower than the previous one. The syntactic approach is the more general one, but it fails to specify when information is meaningful to an agent, which is the focus of the semantic and pragmatic approaches. The network-based approach, meanwhile, provides a framework to understand information use among agents. Badia then explores the consequences of understanding information as existing at several levels. Humans live at the semantic and pragmatic level (and at the network level as a society), computers at the syntactic level. This sheds light on some recent issues, including "fake news" (computers cannot tell whether a statement is true or not, because truth is a semantic notion) and "algorithmic bias" (a pragmatic, not syntactic concern). Humans, not computers, the book argues, have the ability to solve these issues.