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Presentation 020610 New media

Presentation 020610 New media

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  • Literature: we searched for example LISTA, a bibliographical database for library and information sciences, Sociological Abstracts, for social sciences, and
  • Print editions of scholarly journals are becoming a ‘thing of the past’ But, distributed in different digital libraries: we have more than 300 databases, ranging from full-text (Sage), biographical (PubMed), research data etc, repositories, scattered among university, individual open access journals. Where do you start your search?
  • And when you search in Google Scholar or sEURch, which are integrated search engines, covering a lot of databases, you get so many results! You can’t read them all!
  • So there are a number of problems. Human information processing capacity is according to some just 300 kb per day! Computers can’t think for us, they use their own language
  • What do researchers want, or what would be the ideal situation? We want to find what’s relevant but with as less irrelevant articles as possible: Part A should be as big as possible, and Part B and D as little as possible. (picture is borrowed from
  • When you search with the term mouse the relevant articles will be different among scholars from different disciplines.
  • Transcript

    • 1. Digital collections of academic libraries and semantic support Examples, potentials and challenges Judith Gulpers
    • 2. Overview
      • What’s the problem?
      • Possible solutions found in the literature
      • About the literature
    • 3.  
    • 4. You can’t read them all!
    • 5. What’s the problem?
      • Where do you search?
      • Human information processing capacity is limited
      • Computers don’t speak ‘human’.
    • 6. What’s the problem?
      • High recall and high precision are needed: finding the relevant articles with not much irrelevant articles.
      • For a scholar relevancy depends on his needs, interests, and context of the search.
      • In databases: Articles are ranked on relevancy, but that relevancy is calculated.
      • Because: the computer doesn’t understand the query
    • 7. An example
      • ‘ Mouse’
      For a biologist: Mus musculus For a computer scientist: a computer device For a psychologist: test animal For a doctor: cause of RSI
    • 8. The solution?
      • Semantic support
        • gives meaning to information so that humans and computers can work together
        • metadata (data about data) is added and shared between multiple applications
        • computers can read this metadata, because it is put in an ontology
        • ontology: “formally describes concepts and relationships which can exist between them in some community”
    • 9. Semantics between digital libraries
      • Digital libraries already have a lot of semantic support: search by author, title words, keywords from a thesaurus, etc.
      • The problem: communication between the DLs
      • An example: Vascode portal
      • Creating cross-cordanance between different vocabularies - A lot of human work!
      • Does it work?! Not visible in /
    • 10. Semantics for research data
      • UK project ‘policy grid’: concentrates on research data (questionnaires and interviews) collected for evidence-based policy research
      • Ontologies were created for the context of the data: who collected the data, how, when and where
      • But what about the content of the data?
      • Researchers: don’t even try to make an ontology!
      • Their solution: researchers add their own tags, that will create a folksonomy
    • 11. Searching ín articles
      • Automatic indexing of documents
      • Software creates a fingerprint of the document: representation of the characteristic concepts in a text
      • Thesauri are used to ‘tell’ the software what are the characteristic concepts within a certain domain
      • The search results can be visualized, helping you to see the concepts used a lot (or not), helping you find articles
    • 12. About the literature
      • Our startingpoint:
        • What role can social scientists play in enhancing the digital libraries?
      • The literature is mostly written by computer scientists and véry technical
      • Are the computer scientists even telling the scholars what they are doing??
      • Can libraries can play a role in this, as intermediate?