Search (112 results, page 1 of 6)

0.057835408 = product of:
  0.115670815 = sum of:
    0.051931016 = weight(_text_:reference in 1575) [ClassicSimilarity], result of:
      0.051931016 = score(doc=1575,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.2696973 = fieldWeight in 1575, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.046875 = fieldNorm(doc=1575)
    0.0637398 = product of:
      0.1274796 = sum of:
        0.1274796 = weight(_text_:file in 1575) [ClassicSimilarity], result of:
          0.1274796 = score(doc=1575,freq=4.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.5025058 = fieldWeight in 1575, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.046875 = fieldNorm(doc=1575)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The purpose of this paper is to enhance cultural heritage data curation. A core research question of this study is how to share cultural heritage data by using ontologies. A case study was conducted using open government data mapped with the CIDOC-CRM (Conceptual Reference Model). Twelve library-related files in unstructured data format were collected from an open government website, Seoul Metropolitan Government of Korea (http://data.seoul.go.kr). By using the ontologies of the CIDOC CRM 5.1.2, we conducted a mapping process as a way of enhancing cultural heritage information to share information as a data component. We graphed each file then mapped each file in tables. Implications of this study are both the enhanced discoverability of unstructured data and the reusability of mapped information. Issues emerging from this study involve verification of detail for complete compatibility without further input from domain experts.

0.041514903 = product of:
  0.08302981 = sum of:
    0.060586188 = weight(_text_:reference in 6128) [ClassicSimilarity], result of:
      0.060586188 = score(doc=6128,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31464687 = fieldWeight in 6128, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0546875 = fieldNorm(doc=6128)
    0.02244362 = product of:
      0.04488724 = sum of:
        0.04488724 = weight(_text_:22 in 6128) [ClassicSimilarity], result of:
          0.04488724 = score(doc=6128,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.2708308 = fieldWeight in 6128, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6128)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Discusses the goals and outcome of the OCLC/NCSA Metadata Workshop, held in Dublin, Ohio, 1-3 Mar 95, which resulted in the proposed 'Dublin Core' Metadata Elements. Describes an attempt to map the Dublin Core data elements to the USMARC format (with particular reference to USMARC field 856 for electronic locations), noting problems and outstanding questions. The USMARC format elements considered include: subject, title, author, other-agent, publisher, publication date, identifier, object-type, form, relation, language, source, coverage, and other issues

Series

Cataloging and classification quarterly; vol.22, nos.3/4

0.041514903 = product of:
  0.08302981 = sum of:
    0.060586188 = weight(_text_:reference in 180) [ClassicSimilarity], result of:
      0.060586188 = score(doc=180,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31464687 = fieldWeight in 180, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0546875 = fieldNorm(doc=180)
    0.02244362 = product of:
      0.04488724 = sum of:
        0.04488724 = weight(_text_:22 in 180) [ClassicSimilarity], result of:
          0.04488724 = score(doc=180,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.2708308 = fieldWeight in 180, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=180)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

A variety of information communities have developed metadata schemes to meet the needs of their own users. The ability of libraries to incorporate and use multiple metadata schemes in current library systems will depend on the compatibility of imported data with existing catalog data. Authority control will play an important role in metadata interoperability. In this article, I discuss factors for successful authority control in current library catalogs, which include operation in a well-defined and bounded universe, application of principles and standard practices to access point creation, reference to authoritative lists, and bibliographic record creation by highly trained individuals. Metadata characteristics and environmental models are examined and the likelihood of successful authority control is explored for a variety of metadata environments.

Date

10. 9.2000 17:38:22

0.03855694 = product of:
  0.07711388 = sum of:
    0.03462068 = weight(_text_:reference in 3965) [ClassicSimilarity], result of:
      0.03462068 = score(doc=3965,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.17979822 = fieldWeight in 3965, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.03125 = fieldNorm(doc=3965)
    0.0424932 = product of:
      0.0849864 = sum of:
        0.0849864 = weight(_text_:file in 3965) [ClassicSimilarity], result of:
          0.0849864 = score(doc=3965,freq=4.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.33500385 = fieldWeight in 3965, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.03125 = fieldNorm(doc=3965)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

This paper describes recent initiatives to make standard library metadata models and structures available to the Semantic Web, including IFLA standards such as Functional Requirements for Bibliographic Records (FRBR), Functional Requirements for Authority Data (FRAD), and International Standard Bibliographic Description (ISBD) along with the infrastructure that supports them. The FRBR Review Group is currently developing representations of FRAD and the entityrelationship model of FRBR in resource description framework (RDF) applications, using a combination of RDF, RDF Schema (RDFS), Simple Knowledge Organisation System (SKOS) and Web Ontology Language (OWL), cross-relating both models where appropriate. The ISBD/XML Task Group is investigating the representation of ISBD in RDF. The IFLA Namespaces project is developing an administrative and technical infrastructure to support such initiatives and encourage uptake of standards by other agencies. The paper describes similar initiatives with related external standards such as RDA - resource description and access, REICAT (the new Italian cataloguing rules) and CIDOC Conceptual Reference Model (CRM). The DCMI RDA Task Group is working with the Joint Steering Committee for RDA to develop Semantic Web representations of RDA structural elements, which are aligned with FRBR and FRAD, and controlled metadata content vocabularies. REICAT is also based on FRBR, and an object-oriented version of FRBR has been integrated with CRM, which itself has an RDF representation. CRM was initially based on the metadata needs of the museum community, and is now seeking extension to the archives community with the eventual aim of developing a model common to the main cultural information domains of archives, libraries and museums. The Vocabulary Mapping Framework (VMF) project has developed a Semantic Web tool to automatically generate mappings between metadata models from the information communities, including publishers. The tool is based on several standards, including CRM, FRAD, FRBR, MARC21 and RDA.
The paper discusses the importance of these initiatives in releasing as linked data the very large quantities of rich, professionally-generated metadata stored in formats based on these standards, such as UNIMARC and MARC21, addressing such issues as critical mass for semantic and statistical inferencing, integration with user- and machine-generated metadata, and authenticity, veracity and trust. The paper also discusses related initiatives to release controlled vocabularies, including the Dewey Decimal Classification (DDC), ISBD, Library of Congress Name Authority File (LCNAF), Library of Congress Subject Headings (LCSH), Rameau (French subject headings), Universal Decimal Classification (UDC), and the Virtual International Authority File (VIAF) as linked data. Finally, the paper discusses the potential collective impact of these initiatives on metadata workflows and management systems.

0.030293094 = product of:
  0.121172376 = sum of:
    0.121172376 = weight(_text_:reference in 2251) [ClassicSimilarity], result of:
      0.121172376 = score(doc=2251,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.62929374 = fieldWeight in 2251, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.109375 = fieldNorm(doc=2251)
  0.25 = coord(1/4)

0.030293094 = product of:
  0.121172376 = sum of:
    0.121172376 = weight(_text_:reference in 3468) [ClassicSimilarity], result of:
      0.121172376 = score(doc=3468,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.62929374 = fieldWeight in 3468, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.109375 = fieldNorm(doc=3468)
  0.25 = coord(1/4)

0.029653504 = product of:
  0.05930701 = sum of:
    0.04327585 = weight(_text_:reference in 2624) [ClassicSimilarity], result of:
      0.04327585 = score(doc=2624,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.22474778 = fieldWeight in 2624, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2624)
    0.016031157 = product of:
      0.032062314 = sum of:
        0.032062314 = weight(_text_:22 in 2624) [ClassicSimilarity], result of:
          0.032062314 = score(doc=2624,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.19345059 = fieldWeight in 2624, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2624)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

This paper describes the information properties of museum specimen labels and machine learning tools to automatically extract Darwin Core (DwC) and other metadata from these labels processed through Optical Character Recognition (OCR). The DwC is a metadata profile describing the core set of access points for search and retrieval of natural history collections and observation databases. Using the HERBIS Learning System (HLS) we extract 74 independent elements from these labels. The automated text extraction tools are provided as a web service so that users can reference digital images of specimens and receive back an extended Darwin Core XML representation of the content of the label. This automated extraction task is made more difficult by the high variability of museum label formats, OCR errors and the open class nature of some elements. In this paper we introduce our overall system architecture, and variability robust solutions including, the application of Hidden Markov and Naïve Bayes machine learning models, data cleaning, use of field element identifiers, and specialist learning models. The techniques developed here could be adapted to any metadata extraction situation with noisy text and weakly ordered elements.

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

0.026795097 = product of:
  0.10718039 = sum of:
    0.10718039 = sum of:
      0.07511807 = weight(_text_:file in 4550) [ClassicSimilarity], result of:
        0.07511807 = score(doc=4550,freq=2.0), product of:
          0.25368783 = queryWeight, product of:
            5.3600616 = idf(docFreq=564, maxDocs=44218)
            0.047329273 = queryNorm
          0.29610437 = fieldWeight in 4550, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.3600616 = idf(docFreq=564, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4550)
      0.032062314 = weight(_text_:22 in 4550) [ClassicSimilarity], result of:
        0.032062314 = score(doc=4550,freq=2.0), product of:
          0.16573904 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047329273 = queryNorm
          0.19345059 = fieldWeight in 4550, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4550)
  0.25 = coord(1/4)

Abstract

In 2016, the University of Waterloo began offering a mediated copyright review and deposit service to support the growth of our institutional repository UWSpace. This resulted in the need to batch import large lists of published works into the institutional repository quickly and accurately. A range of methods have been proposed for harvesting publications metadata en masse, but many technological solutions can easily become detached from a workflow that is both reproducible for support staff and applicable to a range of situations. Many repositories offer the capacity for batch upload via CSV, so our method provides a template Python script that leverages the Habanero library for populating CSV files with existing metadata retrieved from the CrossRef API. In our case, we have combined this with useful metadata contained in a TSV file downloaded from Web of Science in order to enrich our metadata as well. The appeal of this 'low-maintenance' method is that it provides more robust options for gathering metadata semi-automatically, and only requires the user's ability to access Web of Science and the Python program, while still remaining flexible enough for local customizations.

Date

10.11.2018 16:27:22

0.022768958 = product of:
  0.09107583 = sum of:
    0.09107583 = product of:
      0.18215166 = sum of:
        0.18215166 = weight(_text_:file in 3287) [ClassicSimilarity], result of:
          0.18215166 = score(doc=3287,freq=6.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.71801496 = fieldWeight in 3287, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3287)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Describes the work undertaken by the Wiliam Blake Archive, Virginia University, to document the metadata tools for handling digital images of illustrations accompanying Blake's work. Images are encoded in both JPEG and TIFF formats. Image Documentation (ID) records are slotted into that portion of the JPEG file reserved for textual metadata. Because the textual content of the ID record now becomes part of the image file itself, the documentary metadata travels with the image even it it is downloaded from one file to another. The metadata is invisible when viewing the image but becomes accessible to users via the 'info' button on the control panel of the Java applet

0.01836039 = product of:
  0.07344156 = sum of:
    0.07344156 = weight(_text_:reference in 2222) [ClassicSimilarity], result of:
      0.07344156 = score(doc=2222,freq=4.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.38140965 = fieldWeight in 2222, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.046875 = fieldNorm(doc=2222)
  0.25 = coord(1/4)

Abstract

Describes the structure of metadata formats with particular reference to the taxonomy of data formats set out by the BIBLINK report of the UK Office for Library and Information Networking and based on their underlying complexity. Referes to 3 main types of metadata: Dublin Core; MARC and Federal Geographic Data Committee (FGDC). Provides practical examples of the actual codings used, illustrated with reference to the Dublin Core, Marc and FGDC elements in selected Web sites. Ends with a glossary and a list of Web sites containing background information on metadata, such as the IAMSLIC metadata homepage

0.01626354 = product of:
  0.06505416 = sum of:
    0.06505416 = product of:
      0.13010833 = sum of:
        0.13010833 = weight(_text_:file in 1763) [ClassicSimilarity], result of:
          0.13010833 = score(doc=1763,freq=6.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.5128678 = fieldWeight in 1763, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1763)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Normdaten sind Metadaten besonderer Oualität: Metadaten zu Metadaten. In einem getrennt vom Metadaten-Set zur einzelnen Publikation gebildeten Normdaten-Satz werden die unterschiedlichen in den Publikationen verwendeten Namensformen bzw. Bezeichnungen für dasselbe Objekt zusammengeführt und normiert. Durch die Verwendung von Normdaten als Metadaten wird kontrolliert und sichergestellt, dass z. B. für Autoren, Urheber, Verleger, Sachinhalte etc. gleich bleibende, identische Sucheinstiege und Zugriffspunkte gebildet werden (Authority Control). Für die Recherche wirkt sich die Normierung so aus, dass die zugehörigen Publikationen über alle im Normdatensatz beinhalteten Namensformen und Bezeichnungen gefunden werden können. Durch die Angabe von Attributen und Relationen zu den einzelnen Objekten werden zudem zusätzliche, vernetzte Zugriffspunkte bereitgestellt. Normdaten sind damit ideal zur Bildung von semantischen Navigationsnetzen für die Suche und den Zugriff auf Publikationen und andere Objekte geeignet. Das standardisierte Vokabular und das Nummernsystem einer Normdatei hat aber nur im eigenen Anwendungsbereich Gültigkeit, und die gemeinsame Nutzung von Titeldaten kann durch die Nutzung unterschiedlicher Normdateien behindert werden. Die IFLA-Arbeitsgruppe FRANAR hat mit der Vision eines gemeinsamen Virtuellen Authority File ein Modell entwickelt, wie im Bibliothekswesen Interoperabilität zwischen den nationalen Normdateien hergestellt werden kann. Um die Realisierbarkeit eines solchen Vorhabens nachzuweisen, haben die Library of Congress, OCLC und Die Deutsche Bibliothek ein gemeinsames Projekt vereinbart, in dem exemplarisch für den Bereich der Personennormdaten ein VIAF (Virtual International Authority File) aufgebaut werden soll.

0.01593495 = product of:
  0.0637398 = sum of:
    0.0637398 = product of:
      0.1274796 = sum of:
        0.1274796 = weight(_text_:file in 3865) [ClassicSimilarity], result of:
          0.1274796 = score(doc=3865,freq=4.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.5025058 = fieldWeight in 3865, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.046875 = fieldNorm(doc=3865)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Describes an approach to retrieving environmental sciences information on the Internet using metadatabases. an inf-sheet is created in a flat file system for each resource. The contents of theses sheets are structured by different fields which hold different types of information. 2 classes of information can be distinguished: information describing the content of a resource, which is searchable, and information which links to the resources (URL). A rough automated selection is performed, humans analyze the pre selected resources, and a final selection and indexing is carried out. An algorithm which controle the validity of the meta information is implemented. Describes 2 implemented examples, the Register of Ecological Models and the Metadatabase of Internet Resources

0.015300324 = product of:
  0.061201297 = sum of:
    0.061201297 = weight(_text_:reference in 63) [ClassicSimilarity], result of:
      0.061201297 = score(doc=63,freq=4.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31784135 = fieldWeight in 63, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0390625 = fieldNorm(doc=63)
  0.25 = coord(1/4)

Abstract

Conventional rule-based approaches use exact template matching to capture linguistic information and necessarily need to enumerate all variations. We propose a novel flexible template generation and matching scheme called the principle-based approach (PBA) based on sequence alignment, and employ it for reference metadata extraction (RME) to demonstrate its effectiveness. The main contributions of this research are threefold. First, we propose an automatic template generation that can capture prominent patterns using the dominating set algorithm. Second, we devise an alignment-based template-matching technique that uses a logistic regression model, which makes it more general and flexible than pure rule-based approaches. Last, we apply PBA to RME on extensive cross-domain corpora and demonstrate its robustness and generality. Experiments reveal that the same set of templates produced by the PBA framework not only deliver consistent performance on various unseen domains, but also surpass hand-crafted knowledge (templates). We use four independent journal style test sets and one conference style test set in the experiments. When compared to renowned machine learning methods, such as conditional random fields (CRF), as well as recent deep learning methods (i.e., bi-directional long short-term memory with a CRF layer, Bi-LSTM-CRF), PBA has the best performance for all datasets.

0.015146547 = product of:
  0.060586188 = sum of:
    0.060586188 = weight(_text_:reference in 5096) [ClassicSimilarity], result of:
      0.060586188 = score(doc=5096,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31464687 = fieldWeight in 5096, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5096)
  0.25 = coord(1/4)

Abstract

Since records are timebvound, and contextual metadata must be understood by an observer whose frame of reference is different from that of the recordkeeper, there is a need for external validation. The processes of terminological control, based on definition, are inadequate for this purpose and what is needed is a process of contextual control, based on observation. Ambience is the context of provenance and it is there that we will find external validation of provenance data. Functions offer one possible tool for crafting ambient relationships. Ambient functions define and give meaning to agents of recordkeeping within the context in which they operate and should be distinguished from business activities and processes which do not afford the basis for meaningful discrimination necessary when formulating appraisal categories and useful search patterns

0.015146547 = product of:
  0.060586188 = sum of:
    0.060586188 = weight(_text_:reference in 3201) [ClassicSimilarity], result of:
      0.060586188 = score(doc=3201,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31464687 = fieldWeight in 3201, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3201)
  0.25 = coord(1/4)

Abstract

Outlines the meatadata standard known as the Dublin Core, as well as the Instructional Management Systems Projects, an American Educom NLII initiative which is developing a specification and software for managing online learning resources. Gives the list of fields with brief descriptions from the IMS Metadata Dictionary, and describes the UK Performing Arts Data Service (PADS) workshops on moving image and sound resources with particular reference to the use of the Dublin Core for cataloguing sound recordings. The slow rate of audiovisual progress is touched on: 5 other relevant initiatives connected wit metadata are listed

0.014991195 = product of:
  0.05996478 = sum of:
    0.05996478 = weight(_text_:reference in 1192) [ClassicSimilarity], result of:
      0.05996478 = score(doc=1192,freq=6.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.31141967 = fieldWeight in 1192, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.03125 = fieldNorm(doc=1192)
  0.25 = coord(1/4)

Abstract

In the June 2003 issue of D-Lib Magazine, Kenney et al. (2003) discuss a comparative study between Cornell's email reference staff and Google's Answers service. This interesting study provided insights on the potential impact of "computing and simple algorithms combined with human intelligence" for library reference services. As mentioned in the Kenney et al. article, Bill Arms (2000) had discussed the possibilities of automated digital libraries in an even earlier D-Lib article. Arms discusses not only automating reference services, but also another library function that seems to inspire lively debates about automation-metadata creation. While intended to illuminate, these debates sometimes generate more heat than light. In an effort to explore the potential for automating metadata generation, the Digital Knowledge Center (DKC) of the Sheridan Libraries at The Johns Hopkins University developed and tested an automated name authority control (ANAC) tool. ANAC represents a component of a digital workflow management system developed in connection with the digital Lester S. Levy Collection of Sheet Music. The evaluation of ANAC followed the spirit of the Kenney et al. study that was, as they stated, "more exploratory than scientific." These ANAC evaluation results are shared with the hope of fostering constructive dialogue and discussions about the potential for semi-automated techniques or frameworks for library functions and services such as metadata creation. The DKC's research agenda emphasizes the development of tools that combine automated processes and human intervention, with the overall goal of involving humans at higher levels of analysis and decision-making. Others have looked at issues regarding the automated generation of metadata. A session at the 2003 Joint Conference on Digital Libraries was devoted to automatic metadata creation, and a session at the 2004 conference addressed automated name disambiguation. Commercial vendors such as OCLC, Marcive, and LTI have long used automated techniques for matching names to Library of Congress authority records. We began developing ANAC as a component of a larger suite of open source tools to support workflow management for digital projects. This article describes the goals for the ANAC tool, provides an overview of the metadata records used for testing, describes the architecture for ANAC, and concludes with discussions of the methodology and evaluation of the experiment comparing human cataloging and ANAC-generated results.

0.013602889 = product of:
  0.054411557 = sum of:
    0.054411557 = product of:
      0.10882311 = sum of:
        0.10882311 = weight(_text_:22 in 5743) [ClassicSimilarity], result of:
          0.10882311 = score(doc=5743,freq=4.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.6565931 = fieldWeight in 5743, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=5743)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

30. 3.2002 19:45:22

Source

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

0.013279125 = product of:
  0.0531165 = sum of:
    0.0531165 = product of:
      0.106233 = sum of:
        0.106233 = weight(_text_:file in 5443) [ClassicSimilarity], result of:
          0.106233 = score(doc=5443,freq=4.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.41875482 = fieldWeight in 5443, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5443)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

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.

0.013145663 = product of:
  0.05258265 = sum of:
    0.05258265 = product of:
      0.1051653 = sum of:
        0.1051653 = weight(_text_:file in 2826) [ClassicSimilarity], result of:
          0.1051653 = score(doc=2826,freq=2.0), product of:
            0.25368783 = queryWeight, product of:
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.047329273 = queryNorm
            0.4145461 = fieldWeight in 2826, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.3600616 = idf(docFreq=564, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2826)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Metadata is a resource which can assist the information retrieval of digital documents on the Internet. In designing a metadata system, it is necessary to consider the characteristics of digital documents, such as the variety of file formats, frequent format transformation and the difficulty of distinguishing between the different versions. Provides a brief analysis of some existing metadata formats, and introduces several pronciples for the future development of cataloguing on the Internet. Briefly describes the Metadata Experimental System (MES) currently under development, and located at the author's homepage

0.012982754 = product of:
  0.051931016 = sum of:
    0.051931016 = weight(_text_:reference in 1439) [ClassicSimilarity], result of:
      0.051931016 = score(doc=1439,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.2696973 = fieldWeight in 1439, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.046875 = fieldNorm(doc=1439)
  0.25 = coord(1/4)

Abstract

The relationship between library catalogues and electronic resources differs from that between catalogues and physical materials, particularly with regard to cataloguing rules, which were originally designed to help users of card catalogues to find physical works on library shelves. However, these rules apply awkwardly to electronic resources because functionally different electronic works raise special cataloguinf issues. Discusses the problems of describing remote electronic resources in online catalogues with particular reference to the InterCat project: a nationwide experiment to create a database of Internet resources in MARC format, containing description, location and access information (including PURLs = Persitent URLs)). Concludes that descriptive information helps the user identify the works needed, but that it is practical to provide only minimal desriptive information for remote electronic resources in the catalogue record. To a limited extent, the access lost from reduced description can be replaced with new cataloguing techniques designed to stabilize the catalogue record