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Personal views on what Research Infrastructures really need for data - a more comprehensive version of the 5 minute presentation I have at XLDB-Europe, 8-10th June 2011 in Edinburgh

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  1. 1. What does Research Infrastructure really need for Data?An e-Science infrastructure for biodiversity and ecosystem science ENVRI Common Operations of Environmental Research Infrastructures Alex Hardisty School of Computer Science & Informatics
  2. 2. What is LifeWatch?• European Research Infrastructure for understanding biodiversity as a whole interacting system – Exploring patterns of biodiversity and processes of biodiversity across space/time• A geospatial data e-Infrastructure – Distributed observatories / sensors – Data mgmt., processing and analytical tools – Computational capability and capacity – Collaborative environments – Support, training, partnering, fellowship
  3. 3. Challenge of SCALE: > 25,000 users1800 terrestrial Long- >200 Marine reference and focal Hundreds of millions ofTerm Ecological sites, with more to come: specimens in naturalResearch (LTER) increasingly sensor instrumented science collections:sites: increasingly >275m now indexed,sensor instrumented increasing at 20% p.a.Plus: all kinds of small, personal, group, and departmental datasets that need to get published
  4. 4. From Peterson et al (2010), Syst Biodivers 8(2), 159-168 From Guralnick and Hill (2010), Challenge of HETEROGENEITY: Interconnected nature of biodiversity ideas, outputs, repositories
  5. 5. ENVRI Common solutions to common challenges faced by ESFRI environmental infrastructures(left to right, top to bottom)Global ocean observing infrastructureSvalbard arctic Earth observing systemAircraft for global observing systemTropospheric research aircraftPolar research icebreakerBiodiversity and ecosystem researchMultidisciplinary seafloor observatoryUpgrade of incoherent scatter facilityPlate observing systemIntegrated carbon observation system Source: EC
  6. 6. ENVRI Data transfer Fast data transmission Operation at remote sites User functionalities Data Data Virtual Environments & Collaborative organisations generators users Security & Protection Data discovery & Navigation Data submission tools (meta) data tagging tools Operational Semantic Interoperability Community – specific Services Workflow Generator Knowledge management Virtualisation Persistant storage capacity Data Services 24/7 operation Preservation & Sustainability (digital asset management) Authenticity Certification & Integrity GUIDsSource: W.Los, UvA
  7. 7. ENVRI What do RIs REALLY need for data?• Common solutions to common problems – adopted by each infrastructure through its construction phase• Common Reference Model providing multiple ‘views’ of RI: – Science business / enterprise view, Information view, Computational / services view, Engineering view, Technology view• Standards, Standards, Standards – Data capture from distributed sensors, Metadata definition, Management of high volume data, Execution of workflows, Visualization of data, Provenance and annotation, Interoperability between assets• Common tools e.g., for data discovery and access – in a federation of distributed data repositories and interoperating infrastructures
  8. 8. ENVRI • Report of the High Level Expert Group on Scientific Data • Neelie Kroes, EC Vice-President for the Digital Agenda – “... use it as a reference point when discussing the priorities of EU research investments.”