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Agricultural Learning Repositories & Metadata Application Profiles

Agricultural Learning Repositories & Metadata Application Profiles. Nikos Manouselis , Kostas Kastrantas Informatics Laboratory Div. of Informatics, Mathematics & Statistics Dept. of Science, Agricultural University of Athens GREECE. Digital Learning Repositories.

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Agricultural Learning Repositories & Metadata Application Profiles

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  1. Agricultural Learning Repositories & Metadata Application Profiles Nikos Manouselis, Kostas Kastrantas Informatics Laboratory Div. of Informatics, Mathematics & Statistics Dept. of Science, Agricultural University of Athens GREECE

  2. Digital Learning Repositories • Digital Repository: system for the storage, location and retrieval of digital resources • Digital Learning Repository (DLR): • nature of resources or their description reflects an interest of use in an educational context Holden C., “From Local Challenges to a Global Community: Learning Repositories Summit”, Academic ADL Co-Lab, 2003

  3. A set of questions • Are there DLRs with agricultural content? • Which metadata schemas do they use? • Are there agriculture-specific application profiles? • Relation to AOS?

  4. DLRs for agriculture • Those particularly focusing on agricultural content/stakeholders

  5. DLRs for agriculture • Those particularly focusing on agricultural content/stakeholders • Generic ones that also contain some agricultural content

  6. DLRs for agriculture • Generic ones that also contain some agricultural content

  7. DLRs for agriculture • Those particularly focusing on agricultural content/stakeholders • Generic ones that also contain some agricultural content

  8. Preliminary study • Took place during 2005 • Examined 59 well-known generic DLRs • identified 27DRLs with agricultural content • In a total of ~881,000 educational resources: • …only 3,201 resources (0.36%) related to agricultural topics Tzikopoulos et al., "Investigating Digital Learning Repositories' Coverage of Agriculture-related Topics", ITAFE 2005.

  9. 34.5% of resources not classified (generally: agriculture)

  10. Majority uses a metadata standard (mainly IEEE LOM or LOM based, and Dublin Core)

  11. LR metadata • Learning Technology specifications & standards have been continuously developed since early 1990s • IEEE Learning Object Metadata (LOM) standard widely adopted & implemented • Competing schemas: • DC-ed (but, effort to come closer to LOM) • ISO/IEC JTC1 SC36 LRM (under development)

  12. About IEEE LOM • Nine categories of elements • 76 elements, all optional • Produced by IEEE Learning Technology Standards Committee • adopted as an IEEE standard on 2002 • Past 3 years: studied in depth by ISO/IEC JTC1 SC36 WG4 • Interesting critique: Friesen N. (2004) “International Survey of Learning Object Metadata Implementation” (for ISO/IEC)

  13. LR metadata in agriculture • IEEE LOM application profiles • CG LOM Core (CGIAR) • BEN: Biosci Education Network (AAAS) • BioTune (Netherlands) • …and some of our work: • BIO@GRO LOM AP (organic agriculture) • Organic.Edunet LOM AP (agroecology) • ReGov LOM AP (rural SMEs’ development) • Other approaches • FAO’s Agricultural Learning Resource AP (Ag-LR AP) • ICRICAT, IIT Kanpur, IIT Bombay et al.?

  14. Synergies with AOS • Use AGROVOC for classification purposes inside LRM schemas • Use AGROVOC as a web service • …CGIAR’s DLR already does this • Use an AGROVOC subset/specialization • E.g. AGROVOC-based Agroecology ontology • Implement separately? Include into AGROVOC? • Do special domains require other terms and/or relations? Sanchez-Alonso S. & Sicilia M.-A., “Using an AGROVOC-based ontology for the description of learning resources on organic agriculture”, MTSR 2007.

  15. Potentially interesting… • Harmonization of agricultural LRM • Towards a commonly accepted schema? • Commonly accepted mappings between widely used implementations? (FAO’s Ag-LR AP, CG LOM Core, …) • Connection of agricultural DLRs with federations of generic DLRs • Organic.Edunet federation: • Link to ARIADNE Foundation & GLOBE Consortium • Query propagation using the Simple Query Interface (SQI) • IMS Global Learning Consortium specification (http://www.imsglobal.org/lode.html)

  16. For more information: Nikos Manouselis Informatics LaboratoryAgricultural University of Athensnikosm@ieee.org http://infolab-dev.aua.gr

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