-
Wartburg, K. von; Sibille, C.; Aliverti, C.: Metadata collaboration between the Swiss National Library and research institutions in the field of Swiss historiography (2019)
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- Date
- 30. 5.2019 19:22:49
-
DeZelar-Tiedman, C.: Exploring user-contributed metadata's potential to enhance access to literary works (2011)
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- Date
- 10. 9.2000 17:38:22
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Roy, W.; Gray, C.: Preparing existing metadata for repository batch import : a recipe for a fickle food (2018)
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- Date
- 10.11.2018 16:27:22
-
Willis, C.; Greenberg, J.; White, H.: Analysis and synthesis of metadata goals for scientific data (2012)
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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.
-
Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Hajra, A. et al.: Enriching scientific publications from LOD repositories through word embeddings approach (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Mora-Mcginity, M. et al.: MusicWeb: music discovery with open linked semantic metadata (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
White, H.: Examining scientific vocabulary : mapping controlled vocabularies with free text keywords (2013)
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- Date
- 29. 5.2015 19:09:22
-
Alves dos Santos, E.; Mucheroni, M.L.: VIAF and OpenCitations : cooperative work as a strategy for information organization in the linked data era (2018)
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- Date
- 18. 1.2019 19:13:22
-
Ilik, V.; Storlien, J.; Olivarez, J.: Metadata makeover (2014)
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- Date
- 10. 9.2000 17:38:22
-
Metadata and semantics research : 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings (2016)
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-
Pfister, E.; Wittwer, B.; Wolff, M.: Metadaten - Manuelle Datenpflege vs. Automatisieren : ein Praxisbericht zu Metadatenmanagement an der ETH-Bibliothek (2017)
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- Source
- B.I.T.online. 20(2017) H.1, S.22-25
-
Desconnets, J.-C.; Chahdi, H.; Mougenot, I.: Application profile for earth observation images (2014)
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-
Ashton, J.; Kent, C.: New approaches to subject indexing at the British Library (2017)
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-
Chou, C.: Purpose-driven assessment of cataloging and metadata services : transforming broken links into linked data (2019)
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-
Baker, T.: Dublin Core Application Profiles : current approaches (2010)
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- Source
- Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
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Roux, M.: Metadata for search engines : what can be learned from e-Sciences? (2012)
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- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
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Zapounidou, S.; Sfakakis, M.; Papatheodorou, C.: Library data integration : towards BIBFRAME mapping to EDM (2014)
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-
Birkner, M.; Gonter, G.; Lackner, K.; Kann, B.; Kranewitter, M.; Mayer, A.; Parschalk, A.: Guideline zur Langzeitarchivierung (2016)
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- Abstract
- Guideline zur Hilfestellung für die Langzeitarchivierung von Daten und Objekten im Kontext des Publikations- und Forschungswesens. Diese Guideline soll Hilfestellung für die Langzeitarchivierung von Daten und Objekten im Kontext des Publikations- und Forschungswesens bieten. Sie ist ausdrücklich nicht für den Kontext der Compliance anwendbar. Sie soll dazu ermächtigen, die richtigen Fragen zur Auswahl der für die eigene Institution geeigneten Langzeitarchivierungs-Lösung zu stellen und bei der Entscheidung für eine System-Lösung behilflich sein. Langzeitarchivierungssysteme werden hier als Systeme verstanden, die im Workflow hinter einem Repositorium stehen, in dem digitale Objekte und ihre Metadaten gespeichert und angezeigt werden sowie recherchierbar sind. Allfällige Begriffserklärungen finden Sie im Glossar des Clusters C (Aufbau eines Wissensnetzwerks: Erarbeitung eines Referenzmodells für den Aufbau von Repositorien / Themenbereich Terminologie und Standards).
-
Grün, S.; Poley, C: Statistische Analysen von Semantic Entities aus Metadaten- und Volltextbeständen von German Medical Science (2017)
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