Search (31 results, page 1 of 2)

  • × theme_ss:"Metadaten"
  • × year_i:[2010 TO 2020}
  1. Willis, C.; Greenberg, J.; White, H.: Analysis and synthesis of metadata goals for scientific data (2012) 0.08 
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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.
  2. Rousidis, D.; Garoufallou, E.; Balatsoukas, P.; Sicilia, M.-A.: Evaluation of metadata in research data repositories : the case of the DC.Subject Element (2015) 0.03 
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    Abstract
    Research Data repositories are growing in terms of volume rapidly and exponentially. Their main goal is to provide scientists the essential mechanism to store, share, and re-use datasets generated at various stages of the research process. Despite the fact that metadata play an important role for research data management in the context of these repositories, several factors - such as the big volume of data and its complex lifecycles, as well as operational constraints related to financial resources and human factors - may impede the effectiveness of several metadata elements. The aim of the research reported in this paper was to perform a descriptive analysis of the DC.Subject metadata element and to identify its data quality problems in the context of the Dryad research data repository. In order to address this aim a total of 4.557 packages and 13.638 data files were analysed following a data-preprocessing method. The findings showed emerging trends about the subject coverage of the repository (e.g. the most popular subjects and the authors that contributed the most for these subjects). Also, quality problems related to the lack of controlled vocabulary and standardisation were very common. This study has implications for the evaluation of metadata and the improvement of the quality of the research data annotation process.
  3. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.02 
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    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  4. Hajra, A. et al.: Enriching scientific publications from LOD repositories through word embeddings approach (2016) 0.02 
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    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  5. Mora-Mcginity, M. et al.: MusicWeb: music discovery with open linked semantic metadata (2016) 0.02 
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    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  6. Stiller, J.; Király, P.: Multitlinguality of metadata : measuring the miltilingual degree of Europeana's metadata (2017) 0.01 
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  7. Maurer, M.B.; McCutcheon, S.; Schwing, T.: Who's doing what? : findability and author-supplied ETD metadata in the library catalog (2011) 0.01 
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    Abstract
    Kent State University Libraries' ETD cataloging process features contributions by authors, by the ETDcat application, and by catalogers. Who is doing what, and how much of it is findable in the library catalog? An empirical analysis is performed featuring simple frequencies within the KentLINK catalog, articulated by the use of a newly devised rubric. The researchers sought the degree to which the ETD authors, the applications, and the catalogers can supply accurate, findable metadata. Further development of combinatory cataloging processes is suggested. The method of examining the data and the rubric are provided as a framework for other metadata analysis.
  8. White, H.: Examining scientific vocabulary : mapping controlled vocabularies with free text keywords (2013) 0.01 
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    Date
    29. 5.2015 19:09:22
  9. Alves dos Santos, E.; Mucheroni, M.L.: VIAF and OpenCitations : cooperative work as a strategy for information organization in the linked data era (2018) 0.01 
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    Date
    18. 1.2019 19:13:22
  10. Ilik, V.; Storlien, J.; Olivarez, J.: Metadata makeover (2014) 0.01 
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    Date
    10. 9.2000 17:38:22
  11. Metadata and semantics research : 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings (2016) 0.01 
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  12. Pfister, E.; Wittwer, B.; Wolff, M.: Metadaten - Manuelle Datenpflege vs. Automatisieren : ein Praxisbericht zu Metadatenmanagement an der ETH-Bibliothek (2017) 0.01 
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    Source
    B.I.T.online. 20(2017) H.1, S.22-25
  13. Han, M.-J.K.; Ream-Sotomayor, N.E.; Lampron, P.; Kudeki, D.: "Making Metadata Maker" (2016) 0.01 
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  14. Baker, T.: Dublin Core Application Profiles : current approaches (2010) 0.01 
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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
  15. DeZelar-Tiedman, C.: Exploring user-contributed metadata's potential to enhance access to literary works (2011) 0.01 
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    Date
    10. 9.2000 17:38:22
  16. Wartburg, K. von; Sibille, C.; Aliverti, C.: Metadata collaboration between the Swiss National Library and research institutions in the field of Swiss historiography (2019) 0.01 
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    Date
    30. 5.2019 19:22:49
  17. Pope, J.T.; Holley, R.P.: Google Book Search and metadata (2011) 0.01 
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    Abstract
    This article summarizes published documents on metadata provided by Google for books scanned as part of the Google Book Search (GBS) project and provides suggestions for improvement. The faulty, misleading, and confusing metadata in current Google records can pose potentially serious problems for users of GBS. Google admits that it took data, which proved to be inaccurate, from many sources and is attempting to correct errors. Some argue that metadata is not needed with keyword searching; but optical character recognition (OCR) errors, synonym control, and materials in foreign languages make reliable metadata a requirement for academic researchers. The authors recommend that users should be able to submit error reports to Google to correct faulty metadata.
  18. Kleeck, D. Van; Langford, G.; Lundgren, J.; Nakano, H.; O'Dell, A.J.; Shelton, T.: Managing bibliographic data quality in a consortial academic library : a case study (2016) 0.01 
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    Abstract
    This article presents a case study of quality management for print and electronic resource metadata, summarizing problems and solutions encountered by the Cataloging and Discovery Services Department in the George A. Smathers Libraries at the University of Florida. The authors discuss national, state, and local standards for cataloging, automated and manual record enhancements for data, user feedback, and statewide consortial factors. Findings show that adherence to standards, proactive cleanup of data via manual processes and automated tools, collaboration with vendors and stakeholders, and continual assessment of workflows are key to the management of biblio-graphic data quality in consortial academic libraries.
  19. Kleeck, D. Van; Nakano, H.; Langford, G.; Shelton, T.; Lundgren, J.; O'Dell, A.J.: Managing bibliographic data quality for electronic resources (2017) 0.01 
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    Abstract
    This article presents a case study of quality management issues for electronic resource metadata to assess the support of user tasks (find, select, and obtain library resources) and potential for increased efficiencies in acquisitions and cataloging workflows. The authors evaluated the quality of existing bibliographic records (mostly vendor supplied) for e-resource collections as compared with records for the same collections in OCLC's WorldShare Collection Manager (WCM). Findings are that WCM records better support user tasks by containing more summaries and tables of contents; other checkpoints are largely comparable between the two source record groups. The transition to WCM records is discussed.
  20. Wolfe, EW.: a case study in automated metadata enhancement : Natural Language Processing in the humanities (2019) 0.01 
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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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