Metadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008 will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web -- the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their information in interoperable ways (" participatory metadata") is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice.

Metadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008 will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web -- the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their information in interoperable ways (”participatory metadata”) is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice.

Since it was first published, LIS students and professionals everywhere have relied on Miller’s authoritative manual for clear instruction on the real-world practice of metadata design and creation. Now the author has given his text a top to bottom overhaul to bring it fully up to date, making it even easier for readers to acquire the knowledge and skills they need, whether they use the book on the job or in a classroom. By following this book’s guidance, with its inclusion of numerous practical examples that clarify common application issues and challenges, readers will learn about the concept of metadata and its functions for digital collections, why it’s essential to approach metadata specifically as data for machine processing, and how metadata can work in the rapidly developing Linked Data environment; know how to create high-quality resource descriptions using widely shared metadata standards, vocabularies, and elements commonly needed for digital collections; become thoroughly familiarized with Dublin Core (DC) through exploration of DCMI Metadata Terms, CONTENTdm best practices, and DC as Linked Data; discover what Linked Data is, how it is expressed in the Resource Description Framework (RDF), and how it works in relation to specific semantic models (typically called “ontologies”) such as BIBFRAME, comprised of properties and classes with “domain” and “range” specifications; get to know the MODS and VRA Core metadata schemes, along with recent developments related to their use in a Linked Data setting; understand the nuts and bolts of designing and documenting a metadata scheme; and gain knowledge of vital metadata interoperability and quality issues, including how to identify and clean inconsistent, missing, and messy metadata using innovative tools such as OpenRefine.

This document defines fifteen metadata elements for resource description in a cross-disciplinary information environment.

Part 1 introduces metadata concepts(i. e. understanding metadata and its schemes; metadata and bibliographic control). Part 2 focuses on several metadata schemes such as Dublin Core.

The prevalence of data science has grown exponentially in recent years. Increases in data exchange have created the need for standards and formats on handling data from different sources. Developing Metadata Applications Profiles is an innovative reference source that discusses the latest trends and techniques for effectively managing and exchanging metadata. Including a range of perspectives on schemas and application profiles, such as interoperability, ontology-based design, and model-driven approaches, this book is ideally designed for researchers, academics, professionals, graduate students, and practitioners actively engaged in data science.