Search (10 results, page 1 of 1)

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Date

22. 9.2007 15:41:14

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Date

10. 9.2004 10:22:40

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Date

22. 5.2021 12:43:05

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Abstract

Purpose: Investigate the combination of controlled and folksonomy approaches to support resource discovery in repositories and digital collections. Aim: Investigate whether use of an established controlled vocabulary can help improve social tagging for better resource discovery. Objectives: (1) Investigate indexing aspects when using only social tagging versus when using social tagging with suggestions from a controlled vocabulary; (2) Investigate above in two different contexts: tagging by readers and tagging by authors; (3) Investigate influence of only social tagging versus social tagging with a controlled vocabulary on retrieval. - Vgl.: http://www.ukoln.ac.uk/projects/enhanced-tagging/.

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Abstract

The Black Book Interactive Project at the University of Kansas (KU) is developing an expanded corpus of novels by African American authors, with an emphasis on lesser known writers and a goal of expanding research in this field. Using a custom metadata schema with an emphasis on race-related elements, each novel is analyzed for a variety of elements such as literary style, targeted content analysis, historical context, and other areas. Librarians at KU have worked to develop a variety of computational text analysis processes designed to assist with specific aspects of this metadata collection, including text mining and natural language processing, automated subject extraction based on word sense disambiguation, harvesting data from Wikidata, and other actions.

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Date

10.11.2018 16:27:22

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Abstract

The Dublin Core metadata community and the INDECS/DOI community of authors, rights holders, and publishers are seeking common ground in the expression of metadata for information resources. Recent meetings at the 6th Dublin Core Workshop in Washington DC sketched out common models for semantics (informed by the requirements articulated in the IFLA Functional Requirements for the Bibliographic Record) and conventions for knowledge representation (based on the Resource Description Framework under development by the W3C). Further development of detailed requirements is planned by both communities in the coming months with the aim of fully representing the metadata needs of each. An open "Schema Harmonization" working group has been established to identify a common framework to support interoperability among these communities. The present document represents a starting point identifying historical developments and common requirements of these perspectives on metadata and charts a path for harmonizing their respective conceptual models. It is hoped that collaboration over the coming year will result in agreed semantic and syntactic conventions that will support a high degree of interoperability among these communities, ideally expressed in a single data model and using common, standard tools.

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Date

26.12.2011 14:01:22

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Abstract

For those of us still struggling with basic concepts regarding metadata in this brave new world in which cataloging means much more than MARC, an article like this is welcome indeed. In this 30.000-foot overview of the metadata landscape, broad issues such as modularity, namespaces, extensibility, refinement, and multilingualism are discussed. In addition, "practicalities" like application profiles, syntax and semantics, metadata registries, and automated generation of metadata are explained. Although this piece is not exhaustive of high-level metadata issues, it is nonetheless a useful description of some of the most important issues surrounding metadata creation and use. The rapid changes in the means of information access occasioned by the emergence of the World Wide Web have spawned an upheaval in the means of describing and managing information resources. Metadata is a primary tool in this work, and an important link in the value chain of knowledge economies. Yet there is much confusion about how metadata should be integrated into information systems. How is it to be created or extended? Who will manage it? How can it be used and exchanged? Whence comes its authority? Can different metadata standards be used together in a given environment? These and related questions motivate this paper. The authors hope to make explicit the strong foundations of agreement shared by two prominent metadata Initiatives: the Dublin Core Metadata Initiative (DCMI) and the Institute for Electrical and Electronics Engineers (IEEE) Learning Object Metadata (LOM) Working Group. This agreement emerged from a joint metadata taskforce meeting in Ottawa in August, 2001. By elucidating shared principles and practicalities of metadata, we hope to raise the level of understanding among our respective (and shared) constituents, so that all stakeholders can move forward more decisively to address their respective problems. The ideas in this paper are divided into two categories. Principles are those concepts judged to be common to all domains of metadata and which might inform the design of any metadata schema or application. Practicalities are the rules of thumb, constraints, and infrastructure issues that emerge from bringing theory into practice in the form of useful and sustainable systems.

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Abstract

Over the past three years, the Dublin Core Metadata Initiative has achieved a broad international consensus on the semantics of a simple element set for describing electronic resources. Since the first workshop in March 1995, which was reported in the very first issue of D-Lib Magazine, Dublin Core has been the topic of perhaps a dozen articles here. Originally intended to be simple and intuitive enough for authors to tag Web pages without special training, Dublin Core is being adapted now for more specialized uses, from government information and legal deposit to museum informatics and electronic commerce. To meet such specialized requirements, Dublin Core can be customized with additional elements or qualifiers. However, these refinements can compromise interoperability across applications. There are tradeoffs between using specific terms that precisely meet local needs versus general terms that are understood more widely. We can better understand this inevitable tension between simplicity and complexity if we recognize that metadata is a form of human language. With Dublin Core, as with a natural language, people are inclined to stretch definitions, make general terms more specific, specific terms more general, misunderstand intended meanings, and coin new terms. One goal of this paper, therefore, will be to examine the experience of some related ways to seek semantic interoperability through simplicity: planned languages, interlingua constructs, and pidgins. The problem of semantic interoperability is compounded when we consider Dublin Core in translation. All of the workshops, documents, mailing lists, user guides, and working group outputs of the Dublin Core Initiative have been in English. But in many countries and for many applications, people need a metadata standard in their own language. In principle, the broad elements of Dublin Core can be defined equally well in Bulgarian or Hindi. Since Dublin Core is a controlled standard, however, any parallel definitions need to be kept in sync as the standard evolves. Another goal of the paper, then, will be to define the conceptual and organizational problem of maintaining a metadata standard in multiple languages. In addition to a name and definition, which are meant for human consumption, each Dublin Core element has a label, or indexing token, meant for harvesting by search engines. For practical reasons, these machine-readable tokens are English-looking strings such as Creator and Subject (just as HTML tags are called HEAD, BODY, or TITLE). These tokens, which are shared by Dublin Cores in every language, ensure that metadata fields created in any particular language are indexed together across repositories. As symbols of underlying universal semantics, these tokens form the basis of semantic interoperability among the multiple Dublin Cores. As long as we limit ourselves to sharing these indexing tokens among exact translations of a simple set of fifteen broad elements, the definitions of which fit easily onto two pages, the problem of Dublin Core in multiple languages is straightforward. But nothing having to do with human language is ever so simple. Just as speakers of various languages must learn the language of Dublin Core in their own tongues, we must find the right words to talk about a metadata language that is expressable in many discipline-specific jargons and natural languages and that inevitably will evolve and change over time.