Search (150 results, page 1 of 8)

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Date

10. 9.2000 17:38:22

Type

b

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Source

B.I.T.online. 20(2017) H.1, S.22-25

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Abstract

Multiple authorship is a topic of growing concern in a number of scientific domains. When, as is increasingly common, scholarly articles and clinical reports have scores or even hundreds of authors-what Cronin (in press) has termed "hyperauthorship" -the precise nature of each individual's contribution is often masked. A notation that describes collaborators' contributions and allows those contributions to be tracked in, and across, texts (and over time) offers a solution. Such a notation should be useful, easy to use, and acceptable to communities of scientists. Drawing on earlier work, we present a proposal for an XML-like "contribution" mark-up, and discuss the potential benefits and possible drawbacks

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Abstract

Das Kompetenzzentrum Interoperable Metadaten (KIM) ist eine Informations- und Kommunikationsplattform für Metadatenanwender und -entwickler zur Verbesserung der Interoperabilität von Metadaten im deutschsprachigen Raum. KIM unterstützt und fördert die Erarbeitung von Metadatenstandards, die interoperable Gestaltung von Formaten und damit die optimale Nutzung von Metadaten in digitalen Informationsumgebungen mittels Lehrmaterialien, Schulungen und Beratungen. Das Kompetenzzentrum entsteht im Rahmen des von der Deutschen Forschungsgemeinschaft (DFG) geförderten Projekts KIM unter der Federführung der Niedersächsischen Staats- und Universitätsbibliothek Göttingen (SUB) in Zusammenarbeit mit der Deutschen Nationalbibliothek (DNB). Projektpartner sind in der Schweiz die Hochschule für Technik und Wirtschaft HTW Chur, die Eidgenössische Technische Hochschule (ETH) Zürich und in Österreich die Universität Wien. Aufgabe des Kompetenzzentrums ist es, die Interoperabilität von Metadaten zu verbessern. Interoperabilität ist die Fähigkeit zur Zusammenarbeit von heterogenen Systemen. Datenbestände unabhängiger Systeme können ausgetauscht oder zusammengeführt werden, um z. B. eine systemübergreifende Suche oder das Browsen zu ermöglichen. Daten werden zum Teil in sehr unterschiedlichen Datenbanksystemen gespeichert. Interoperabilität entsteht dann, wenn die Systeme umfangreiche Schnittstellen implementieren, die ein weitgehend verlustfreies Mapping der internen Datenrepräsentation ermöglichen.

Source

Dialog mit Bibliotheken. 20(2008) H.1, S.22-24

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Abstract

Metadata and information technology staff in libraries that are building digital collections typically extract and manipulate MARC metadata sets to provide access to digital content via non-MARC schemes. Metadata processing in these libraries involves defining the relationships between metadata schemes, moving metadata between schemes, and coordinating the intellectual activity and physical resources required to create and manipulate metadata. Actively managing the non-MARC metadata resources used to build digital collections is something most of these libraries have only begun to do. This article proposes strategies for managing MARC metadata repurposing efforts as the first step in a coordinated approach to library metadata management. Guided by lessons learned from Cornell University library mapping and transformation activities, the authors apply the literature of data resource management to library metadata management and propose a model for managing MARC metadata repurposing processes through the implementation of a metadata management design.

Source

Library hi tech. 22(2004) no.2, S.144-152

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Date

10. 9.2000 17:38:22

Type

b

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Abstract

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects. Design/methodology/approach This study's analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians' theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures' suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness. Findings This study's results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity. Originality/value The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study's results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

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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.

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Source

Wissenschaft online: Elektronisches Publizieren in Bibliothek und Hochschule. Hrsg. B. Tröger

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Date

30. 3.2002 19:45:22

Source

Revista Española de Documentaçion Cientifica. 22(1999) no.2, S.198-219

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Date

16. 7.2000 20:58:22

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Source

Library hi tech. 22(2004) no.1

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Source

Online information 96: 20th International online information meeting, Proceedings, London, 3-5 December 1996. Ed.: D.I. Raitt u. B. Jeapes

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Date

28. 3.2002 9:22:34

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Source

Library hi tech. 22(2004) no.1

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Source

Library hi tech. 22(2004) no.2

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Abstract

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.

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