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intro

intro. 3/181. our project. in agINFRA we will: share agricultural research… …over a data e-infrastructure. 7/181. consortium (1/2). 8/181. consortium (2/2). 9/181. overview. Content. Technical. Users. Dissemination. 10/181. agricultural research data. Primary data:

melyssa-garrett
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intro

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  1. intro 3/181

  2. our project in agINFRA we will: share agricultural research… …over a data e-infrastructure 7/181

  3. consortium(1/2) 8/181

  4. consortium(2/2) 9/181

  5. overview Content Technical Users Dissemination 10/181

  6. agricultural research data • 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 • Methods and procedures followed • Reports, including papers • Secondary documents, e.g. training resources • Metadata about the above • Social data, tags, ratings, etc. 17/181

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  8. data infrastructure • layered hardware and software systems • support sharing of wide spectrum of resources • networks, storage, computing resources • system-level middleware software • structured information within collections, archives, databases • principles of global collaboration and shared resources • encompass sharing needs of all research activities 21/181

  9. data infra in ag research • 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 22/181

  10. data infra in ag research • 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 23/181

  11. agINFRA in a few words • based on a linked open data architecture harmonizing semantics and ontologies • aggregating data of existing systems, taking advantage of advanced cloud/grid services and infrastructure • devised for scalability and maximum interoperability by adapting existing widely used components • fostering diverse communities of heterogeneous providers and users 24/181

  12. agINFRAvalues We truly believe that scientific data A | Open | Must be open and interlinked NOT subject to barriers, based on standard formats and avoiding building data silos due to lack of interrelatedness and ad-hoc APIs. B | Meaningful | Must be meaningful through explicit semantics Reusing the semantics already provided in mature terminologies and ontologies that are exposed and interlinked through the Web. C | Reliable | Must be reliable, traceable and accessible Any kind of research objects can be stored in the data infrastructure, and there are NO barriers to expressing relations between these objects to capture the context of research activities. D | Actionable | Must be actionable via services that empower research Data is not useful without flexible and adaptable services that allow researchers to act on the data in the ways they need. 25/181

  13. architecture • Operational architecture • REST API layer • Module layer • Grid layer • Functional architecture • Dataset exposure layer • Data management layer • Data transformation layer • Data processing layer 56/181

  14. Web-based components and services Event subscription API RDF/SPARQL Dataset API Transform API Service APIs agINFRA data infrastructure Dataset exposure layer Data management layer Data transformation layer Data processing layer … Keyphrase extraction Interlinking Harvesting De-duplication Metadata validation 74/181

  15. agINFRA data services • Integrated services (WP6) • Components (WP4) • Infrastructure services (WP3) • agDataHarvest • agGridCrawl • agOCR-PP • agMetaExtract • agBBDataExtract • agKEA • agGridExtract • agDataTransform • agDocSeg • agDeDup • agGridStore • agGridQuery • ag2RDF • agSN&SO 61/181

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