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Shotton miidi at_mibbi_workshop-01_dec2010

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Shotton miidi at_mibbi_workshop-01_dec2010 Shotton miidi at_mibbi_workshop-01_dec2010 Presentation Transcript

  •  
  • The PLoS NTD article Study Summary
    • The Study Summary of our chosen PLoS NTD article:
      • was specific to that individual paper
      • was not in machine-readable form
    • What was required was a proper machine-readable metadata standard that could be used to summarize any infectious disease investigation
  • MIIDI and other MIBBI standards
    • So we have started to develop MIIDI , a Minimal Information standard for reporting an Infectious Disease Investigation
    • MIIDI is designed to provides a metadata check list for investigations relevant to infectious diseases, building on IDO, the Infectious Disease Ontology
    • MIIDI extends the scope of previous MIBBI standards ( Minimum Information for Biological and Biomedical Investigations ), which are largely focused on metadata for research datasets of laboratory origin
      • MIIDI is designed for use in describing both datasets and publications
      • For the latter, it has items not found in any other MIBBI standard
        • e.g. investigation conclusions
    • We had an international MIIDI planning meeting in September 2009, attended by 26 people including Chris Taylor, Susanna Sansone and Dawn Field, representatives of health protection agencies (HPA, WHO), ontologists and other information scientists, STM publishers, clinicians, vets and epidemiologies
    • I have just received short-term JISC funding to permit this work to go forward, and I’m now looking for a suitably qualified researcher to work with me on it
    View slide
  • How will MIIDI help?
    • MIIDI has several potential uses:
      • It can act as a content checklist for authors, editors and reviewers
      • It can underpin machine-readable Structured Digital Abstracts
      • It can ensure metadata for a research dataset is adequate
      • It can underpin tools for metadata creation
      • It can aid resource discovery by providing semantically defined search terms
      • MIIDI metadata files in RDF can facilitate automated data integration
      • MIIDI Structured Digital Abstracts in RDF can facilitate automated publication selection
        • e.g. of clinical trial reports, for systematic reviews
    • To do: Refine the MIIDI model – requires community involvement
    • Define terms using ontologies, so that metadata may be recorded as RDF
    • Test with real-world data, then use routinely
    View slide
  • Minimal Information Standards, Ontologies and Tools Ontologies Minimal Information Standards Define essential metadata components Metadata creation tools e.g. ISA-Creator Datasets Structured digital abstracts machine-readable Articles Metadata-rich datasets Semantically rich papers Sources of structured vocabularies of classes , e.g. ‘protein’ or ‘city’ Sources of disambiguated defined names of instances , e.g. ‘trypsin’ or ‘Salvador’ Gazetteers and CVs