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  • × theme_ss:"Metadaten"
  1. Farney, T.: using Google Tag Manager to share code : Designing shareable tags (2019) 0.06 
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    Abstract
    Sharing code between libraries is not a new phenomenon and neither is Google Tag Manager (GTM). GTM launched in 2012 as a JavaScript and HTML manager with the intent of easing the implementation of different analytics trackers and marketing scripts on a website. However, it can be used to load other code using its tag system onto a website. It's a simple process to export and import tags facilitating the code sharing process without requiring a high degree of coding experience. The entire process involves creating the script tag in GTM, exporting the GTM content into a sharable export file for someone else to import into their library's GTM container, and finally publishing that imported file to push the code to the website it was designed for. This case study provides an example of designing and sharing a GTM container loaded with advanced Google Analytics configurations such as event tracking and custom dimensions for other libraries using the Summon discovery service. It also discusses processes for designing GTM tags for export, best practices on importing and testing GTM content created by other libraries and concludes with evaluating the pros and cons of encouraging GTM use.
    Object
    Google Tag Manager
  2. Kleeck, D. Van; Nakano, H.; Langford, G.; Shelton, T.; Lundgren, J.; O'Dell, A.J.: Managing bibliographic data quality for electronic resources (2017) 0.04 
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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.
  3. Chapman, J.W.; Reynolds, D.; Shreeves, S.A.: Repository metadata : approaches and challenges (2009) 0.04 
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    Abstract
    Many institutional repositories have pursued a mixed metadata environment, relying on description by multiple workflows. Strategies may include metadata converted from other systems, metadata elicited from the document creator or manager, and metadata created by library or repository staff. Additional editing or proofing may or may not occur. The mixed environment brings challenges of creation, management, and access. In this paper, repository efforts at three major universities are discussed. All three repositories run on the DSpace software package, and the opportunities and limitations of that system will be examined. The authors discuss local strategies in light of current thinking on metadata creation, user behavior, and the aggregation of heterogeneous metadata. The contrasts between the mission of each repository effort will show the importance of local customization, while the experience of all three institutions forms the basis for recommendations on strategies of benefit to a wide range of librarians and repository planners.
  4. Pole, T.: Contextual classification in the Metadata Object Manager (M.O.M.) (1999) 0.03 
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    Abstract
    To Classify is (according to Webster's) "to distribute into classes; to arrange according to a system; to arrange in sets according to some method founded on common properties or characters." A model of classification is a type or category or (excuse the recursive definition) a class of classification "system" as mentioned in Webster's definition. One employs a classification model to implement a specific classification system. (E.g. we employ the hierarchical classification model to implement the Dewey Decimal System) An effective classification model must represent both the commonality (Webster's "common properties"), and also the differences among the items being classified. The commonality of each category or class defines a test to determine which items belong to the set that class represents. The relationships among the classes define the variability among the sets that the classification model can represent. Therefore, a classification model is more than an enumeration or other simple listing of the names of its classes. Our purpose in employing classification models is to build metadata systems that represent and manage knowledge, so that users of these systems we build can: quickly and accurately define (the commonality of) what knowledge they require, allowing the user great flexibility in how that desire is described; be presented existing information assets that best match the stated requirements; distinguish (the variability) among the candidates to determine their best choice(s), without actually having to examine the individual items themselves; retrieve the knowledge they need The MetaData model we present is Contextual Classification. It is a synthesis of several traditional metadata models, including controlled keyword indices, hierarchical classification, attribute value systems, Faceted Classification, and Evolutionary Faceted Classification. Research into building on line library systems of software and software documentation (Frakes and Pole, 19921 and Pole 19962) has shown the need and viability of combining the strengths, and minimizing the weaknesses of multiple metadata models in the development of information systems. The MetaData Object Manager (M.O.M.), a MetaData Warehouse (MDW) and editorial work flow system developed for the Thomson Financial Publishing Group, builds on this earlier research. From controlled keyword systems we borrow the idea of representing commonalties by defining formally defined subject areas or categories of information, which sets are represented by these categories names. From hierarchical classification, we borrow the concept of relating these categories and classes to each other to represent the variability in a collection of information sources. From attribute value we borrow the concept that each information source can be described in different ways, each in respect to the attribute of the information being described. From Faceted Classification we borrow the concept of relating the classes themselves into sets of classes, which a faceted classification system would describe as facets of terms. In this paper we will define the Contextual Classification model, comparing it to the traditional metadata models from which it has evolved. Using the MOM as an example, we will then discuss both the use of Contextual Classification is developing this system, and the organizational, performance and reliability
  5. Jimenez, V.O.R.: Nuevas perspectivas para la catalogacion : metadatos ver MARC (1999) 0.03 
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    Date
    30. 3.2002 19:45:22
    Source
    Revista Española de Documentaçion Cientifica. 22(1999) no.2, S.198-219
  6. Andresen, L.: Metadata in Denmark (2000) 0.03 
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    Date
    16. 7.2000 20:58:22
  7. MARC and metadata : METS, MODS, and MARCXML: current and future implications (2004) 0.03 
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    Source
    Library hi tech. 22(2004) no.1
  8. Moen, W.E.: ¬The metadata approach to accessing government information (2001) 0.02 
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    Date
    28. 3.2002 9:22:34
  9. MARC and metadata : METS, MODS, and MARCXML: current and future implications (2004) 0.02 
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    Library hi tech. 22(2004) no.1
  10. MARC and metadata : METS, MODS, and MARCXML: current and future implications part 2 (2004) 0.02 
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    Library hi tech. 22(2004) no.2
  11. Broughton, V.: Automatic metadata generation : Digital resource description without human intervention (2007) 0.02 
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    Date
    22. 9.2007 15:41:14
  12. Caplan, P.; Guenther, R.: Metadata for Internet resources : the Dublin Core Metadata Elements Set and its mapping to USMARC (1996) 0.02 
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    Date
    13. 1.2007 18:31:22
    Source
    Cataloging and classification quarterly. 22(1996) nos.3/4, S.43-58
  13. Tennant, R.: ¬A bibliographic metadata infrastructure for the twenty-first century (2004) 0.02 
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    Date
    9.12.2005 19:22:38
    Source
    Library hi tech. 22(2004) no.2, S.175-181
  14. Hoffmann, L.: Metadaten von Internetressourcen und ihre Integrierung in Bibliothekskataloge (1998) 0.02 
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    22. 5.1998 18:45:36
  15. Essen, F. von: Metadaten - neue Perspektiven für die Erschließung von Netzpublikationen in Bibliotheken : Erster META-LIB-Workshop in Göttingen (1998) 0.02 
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    Content
    Bericht über den Workshop, der am 22. u. 23.6.98 in der SUB Göttingen stattfand
  16. 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
  17. 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
  18. 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
  19. Brugger, J.M.: Cataloging for digital libraries (1996) 0.01 
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    Cataloging and classification quarterly. 22(1996) nos.3/4, S.59-73
  20. Proffitt, M.: Pulling it all together : use of METS in RLG cultural materials service (2004) 0.01 
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    Source
    Library hi tech. 22(2004) no.1, S.65-68

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