Search (13 results, page 1 of 1)

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Abstract

The range of metadata activity over this last decade is both extensive and astonishing, and substantiates metadata as an integral part of our digital information infrastructure. This entry begins with a brief history of metadata relating to digital information, followed by an overview of different metadata types, functions, and domain-specific definitions. Next, the family of standards comprising a metadata architecture are defined, followed by an overview of metadata generation processes, applications, and people: this latter section gives particular attention to automatic metadata generation approaches. The following section explores four key metadata models. The conclusion summarizes the entry, highlights a number of significant metadata challenges, and notes efforts underway to address metadata challenges in the new millennium.

Content

Digital unter: http://dx.doi.org/10.1081/E-ELIS3-120044415. Vgl.: http://www.tandfonline.com/doi/book/10.1081/E-ELIS3.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

The basic goal of education within a discipline is to transform a novice into an expert. This entails moving the novice toward the "semantic space" that the expert inhabits-the space of concepts, meanings, vocabularies, and other intellectual constructs that comprise the discipline. Metadata is significant to this goal in digitally mediated education environments. Encoding the experts' semantic space not only enables the sharing of semantics among discipline scientists, but also creates an environment that bridges the semantic gap between the common vocabulary of the novice and the granular descriptive language of the seasoned scientist (Greenberg, et al, 2005). Developments underlying the Semantic Web, where vocabularies are formalized in the Web Ontology Language (OWL), and Web 2.0 approaches of user-generated folksonomies provide an infrastructure for linking vocabulary systems and promoting group learning via metadata literacy. Group learning is a pedagogical approach to teaching that harnesses the phenomenon of "collective intelligence" to increase learning by means of collaboration. Learning a new semantic system can be daunting for a novice, and yet it is integral to advance one's knowledge in a discipline and retain interest. These ideas are key to the "BOT 2.0: Botany through Web 2.0, the Memex and Social Learning" project (Bot 2.0).72 Bot 2.0 is a collaboration involving the North Carolina Botanical Garden, the UNC SILS Metadata Research center, and the Renaissance Computing Institute (RENCI). Bot 2.0 presents a curriculum utilizing a memex as a way for students to link and share digital information, working asynchronously in an environment beyond the traditional classroom. Our conception of a memex is not a centralized black box but rather a flexible, distributed framework that uses the most salient and easiest-to-use collaborative platforms (e.g., Facebook, Flickr, wiki and blog technology) for personal information management. By meeting students "where they live" digitally, we hope to attract students to the study of botanical science. A key aspect is to teach students scientific terminology and about the value of metadata, an inherent function in several of the technologies and in the instructional approach we are utilizing. This poster will report on a study examining the value of both folksonomies and taxonomies for post-secondary college students learning plant identification. Our data is drawn from a curriculum involving a virtual independent learning portion and a "BotCamp" weekend at UNC, where students work with digital plan specimens that they have captured. Results provide some insight into the importance of collaboration and shared vocabulary for gaining confidence and for student progression from novice to expert in botany.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

Metadata generation is the act of creating or producing metadata. Generating good quality metadata in an efficient manner is essential for organizing and making accessible the growing number of rich resources available an the Web. The success of digital libraries, the sustenance of interoperability - as promoted by the Open Archives Initiative - and the evolution of Semantic Web all rely an efficient metadata generation. This article sketches a metadata generation framework that involves processes, people and tools. It also presents selected research initiatives and highlights the goals of the Metadata Generation Research Project.

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Abstract

Metadata is of paramount importance for persons, organizations, and endeavors of every dimension that are increasingly turning to the World Wide Web (hereafter referred to as the Web) as a chief conduit for accessing and disseminating information. This is evidenced by the development and implementation of metadata schemas supporting projects ranging from restricted corporate intranets, data warehouses, and consumer-oriented electronic commerce enterprises to freely accessible digital libraries, educational initiatives, virtual museums, and other public Web sites. Today's metadata activities are unprecedented because they extend beyond the traditional library environment in an effort to deal with the Web's exponential growth. This article considers metadata in today's Web environment. The article defines metadata, examines the relationship between metadata and cataloging, provides definitions for key metadata vocabulary terms, and explores the topic of metadata generation. Metadata is an extensive and expanding subject that is prevalent in many environments. For practical reasons, this article has elected to concentrate an the information resource domain, which is defined by electronic textual documents, graphical images, archival materials, museum artifacts, and other objects found in both digital and physical information centers (e.g., libraries, museums, record centers, and archives). To show the extent and larger application of metadata, several examples are also drawn from the data warehouse, electronic commerce, open source, and medical communities.

Source

Encyclopedia of library and information science. Vol.72, [=Suppl.35]

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Abstract

This report presents recent metadata developments for Dryad, a digital repository hosting datasets underlying publications in the field of evolutionary biology. We review our efforts to bring the Dryad application profile into conformance with the Singapore Framework and discuss practical issues underlying the application profile implementation in a DSpace environment. The report concludes by outlining the next steps planned as Dryad moves into the next phase of development.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Source

Journal of digital information. 2(2002) no.2,

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Abstract

Knowledge Organization Systems (KOS) as networks of knowledge have the potential to inform AI operations. This paper explores natural language processing and machine learning in the context of KOS and Helping Interdisciplinary Vocabulary Engineering (HIVE) technology. The paper presents three use cases: HIVE and Historical Knowledge Networks, HIVE for Materials Science (HIVE-4-MAT), and Using HIVE to Enhance and Explore Medical Ontologies. The background section reviews AI foundations, while the use cases provide a frame of reference for discussing current progress and implications of connecting KOS to AI in digital resource collections.

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Abstract

This article explores the applicability primary library functions (collection development, cataloging, reference, and circulation) to the Semantic Web. The article defines the Semantic Web, identifies similarities between the library institution and the Semantic Web, and presents research questions guiding the inquiry. The article addresses each library function and demonstrates the applicability of each function's polices to Semantic Web development. Results indicate that library functions are applicable to Semantic Web, with "collection development" translating to "Semantic Web selection;" "cataloging" translating to "Semantic Web 'semantic' representation;" "reference" translating to "Semantic Web service," and circulation translating to "Semantic Web resource use." The last part of this article includes a discussion about the lack of embrace between the library and the Semantic Web communities, recommendations for improving this gap, and research conclusions.

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Object

Library of Congress thesaurus for graphical materials

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Abstract

This research explores temporal concept drift and temporal alignment in knowledge organization systems (KOS). A comparative analysis is pursued using the 1910 Library of Congress Subject Headings, 2020 FAST Topical, and automatic indexing. The use case involves a sample of 90 nineteenth-century Encyclopedia Britannica entries. The entries were indexed using two approaches: 1) full-text indexing; 2) Named Entity Recognition was performed upon the entries with Stanza, Stanford's NLP toolkit, and entities were automatically indexed with the Helping Interdisciplinary Vocabulary application (HIVE), using both 1910 LCSH and FAST Topical. The analysis focused on three goals: 1) identifying results that were exclusive to the 1910 LCSH output; 2) identifying terms in the exclusive set that have been deprecated from the contemporary LCSH, demonstrating temporal concept drift; and 3) exploring the historical significance of these deprecated terms. Results confirm that historical vocabularies can be used to generate anachronistic subject headings representing conceptual drift across time in KOS and historical resources. A methodological contribution is made demonstrating how to study changes in KOS over time and improve the contextualization historical humanities resources.

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Abstract

Purpose - The purpose of this paper is to examine the effect of the Helping Interdisciplinary Vocabulary Engineering (HIVE) system on the inter-indexer consistency of information professionals when assigning keywords to a scientific abstract. This study examined first, the inter-indexer consistency of potential HIVE users; second, the impact HIVE had on consistency; and third, challenges associated with using HIVE. Design/methodology/approach - A within-subjects quasi-experimental research design was used for this study. Data were collected using a task-scenario based questionnaire. Analysis was performed on consistency results using Hooper's and Rolling's inter-indexer consistency measures. A series of t-tests was used to judge the significance between consistency measure results. Findings - Results suggest that HIVE improves inter-indexing consistency. Working with HIVE increased consistency rates by 22 percent (Rolling's) and 25 percent (Hooper's) when selecting relevant terms from all vocabularies. A statistically significant difference exists between the assignment of free-text keywords and machine-aided keywords. Issues with homographs, disambiguation, vocabulary choice, and document structure were all identified as potential challenges. Research limitations/implications - Research limitations for this study can be found in the small number of vocabularies used for the study. Future research will include implementing HIVE into the Dryad Repository and studying its application in a repository system. Originality/value - This paper showcases several features used in HIVE system. By using traditional consistency measures to evaluate a semantic web technology, this paper emphasizes the link between traditional indexing and next generation machine-aided indexing (MAI) tools.

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Abstract

The proliferation of discipline-specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed-methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata-related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05). Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have "scheme harmonization" (compatibility and interoperability with related schemes) as an objective; schemes with the objective "abstraction" (a conceptual model exists separate from the technical implementation) also have the objective "sufficiency" (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective "data publication" do not have the objective "element refinement." The analysis indicates that many metadata-driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata-related research, particularly in the context of recent funding agency policy changes.