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Large-scale (meta)Data Aggregators & Infrastructure Requirements the case of agriculture

Large-scale (meta)Data Aggregators & Infrastructure Requirements the case of agriculture. Nikos Manouselis Agro-Know Technologies & ARIADNE Foundation nikosm@ieee.org @eAGE 2012, Dubai, 13/12/12. (agricultural) research data. Publications, theses, reports, other grey literature

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Large-scale (meta)Data Aggregators & Infrastructure Requirements the case of agriculture

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  1. Large-scale (meta)Data Aggregators & Infrastructure Requirementsthe case of agriculture Nikos Manouselis Agro-Know Technologies & ARIADNE Foundation nikosm@ieee.org @eAGE 2012, Dubai, 13/12/12

  2. (agricultural) research data • Publications, theses, reports, other grey literature • Educational material and content, courseware • Primary data: • Structured, e.g. datasets as tables • Digitized : images, videos, etc. • Secondary data (elaborations, e.g. a dendogram) • Provenance information, incl. authors, their organizations and projects • Experimental protocos & methods • Social data, tags, ratings, etc.

  3. educators’ view stats gene banks gis data blogs, journals open archives raw data technologies learning objects ………..

  4. researchers’ view stats gene banks gis data blogs, journals open archives raw data technologies learning objects ………..

  5. practioners’ view stats gene banks gis data blogs, journals open archives raw data technologies learning objects ………..

  6. data infrastructure for agriculture • aim is: promoting data sharing and consumption related to any research activity aimed at improving productivity and quality of crops ICT for computing, connectivity, storage, instrumentation

  7. data infrastructure for agriculture • aim is: promoting datasharing and consumption related to any research activity aimed at improving productivity and quality of crops ICT for computing, connectivity, storage, instrumentation

  8. Author Subject ID Title Publisher Date Catalog we actually share metadata

  9. e.g. an educational resource

  10. …metadata reflect the context

  11. …sometimes, data also included

  12. metadata aggregations • concerns viewing mergedcollections of metadata records from different sources • useful: when access to specific supersets or subsets of networked collections • records actually stored at aggregator • or queries distributed at virtually aggregated collections

  13. typically look like this Ternier et al., 2010

  14. typical problem: computing

  15. typical problem: hosting

  16. an ideal scenario

  17. Data provider in need of hosting & storage of small-scale CMS sets upown CMS instance requests space/accounts in large-scale CMS Data provider in need of large scale hosting & replication CMS Data provider hosting CMS at own or external/commercial infrastructure register as data source hosted over cloud register as data source hosted over cloud interested to expose (meta)data to e-infrastructure register as data source computed over grid

  18. indexed & available throughCIARD RING (META)DATA AGGREGATOR shares (meta)data e.g. through OAI-PMH computed over grid & hosted over cloud shares (meta)data e.g. through OAI-PMH supported by scientific gateway shares (meta)data e.g. through OAI-PMH computed & hosted over agINFRA grid/cloud

  19. computed over grid computed over grid computed over grid & hosted over cloud …

  20. overall need • its all about efficient metadata management • storage issues: where components are hosted, how metadata aggregations & their versions handled/stored, scaling up • computing issues: harvesting takes time/resources and needs to be invoked often, automatic tagging tasks demanding • often recurring, similar workflows are needed (validate, transform, harvest, auto-tag, index)

  21. why should you care?

  22. promoting course descriptions • push course information to various syndication/aggregation sites to allow users discover them • OCW search engine (http://www.ocwsearch.com) • Moodle Hub concept (hub.moodle.org)

  23. including relevant content • allow course creator/author to find relevant material and resources to enrich course • Europeana ingestion widget (http://wiki.agroknow.gr/agroknow/index.php/Hack4Europe_2012) • suggest to learners additional courses and material relevant to what they access • Eummena’s Moodle Widget (http://www.eummena.org/index.php/labs)

  24. developing more end-user services • Web portals to support user communities (e.g. thematic, geographical, social, cultural) • MACE portal (http://portal.mace-project.eu) • Photodentro Greek school collections portal (http://photodentro.edu.gr) • VOA3R social platform for researchers (http://voa3r.cc.uah.es)

  25. wrap up

  26. (META)DATA AGGREGATOR

  27. considerations • easily replicated cloud-hosted software applications (e.g. DSPACE instances) • portal/service owners and software developers to use the infrastructure as a basis • power up existing data & service networks

  28. interesting: TERENA OER pilot • interconnecting open educational resource repositories of NRENs https://confluence.terena.org/pages/viewpage.action?pageId=33751325

  29. interesting: GLOBE • Global Learning Objects Brokering Exchange Alliance • http://globe-info.org

  30. thank you! nikosm@ieee.org http://wiki.agroknow.gr http://ariadne-eu.org

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