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EarthCube DDMA AGU

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EarthCube DDMA AGU

  1. 1. A Community Roadmap for EnablingAccess to Geosciences DataTanu MalikIan FosterComputation InstituteUniversity of Chicago and Argonne National Lab.tanum@ci.uchicago.edu, foster@anl.gov www.ci.anl.gov www.ci.uchicago.edu
  2. 2. Outline• Access Workshop• DataSpace• Post Charette EarthCube www.ci.anl.gov2 www.ci.uchicago.edu
  3. 3. Access is Vital for EarthCube’s Success• The goal of EarthCube is to create a sustainable infrastructure that enables the sharing of all geosciences data, information, and knowledge in an open, transparent and inclusive manner. I cant get access to *. It is difficult for me to *. I want to integrate data from other disciplines, but *. Access refers to software and activities that make data and computational resources easily, efficiently and reliably available to scientists across disciplines. www.ci.anl.gov3 www.ci.uchicago.edu
  4. 4. Access Workshop Goals• Encourage discussions on emergent issues: – Use of cloud computing – Exploiting the general principle of moving computation to data – A technological and governance framework for cross-disciplinary access, service architecture, brokering principles, real-time data, uniform authentication and authorization environment, etc. – Improving access to data in publications.• Bring some standardization on research data life cycle issues: – In general, data, once generated, follow a lifecycle---they are stored, described, processed, transformed, accessed, discovered, analyze d, and curated. In organized networks and campaigns, lifecycle stages are often documented and standardized, though vary significantly across networks and campaigns. In individual initiatives, the lifecycle stages continue to remain ad hoc and ill-defined. [RDLM-Workshop2011]• Obtain community consensus on a few use cases www.ci.anl.gov4 www.ci.uchicago.edu
  5. 5. Workshop Activity Outcomes• Use Case 1: Can I access “not large” but “big data” to conduct statistical analysis?• Use Case 2: I have a hypothesis not tied to a physical instrument or geophysical parameter. Can I still access all the data, in an “interactive” fashion to test my hypothesis?• Use Case 3: The storm dust paper is vital to my research. Can I access the data in the publication and change parameters of experiments to understand the nature of storm dust? www.ci.anl.gov5 www.ci.uchicago.edu
  6. 6. Workshop Reflections• Its all about data! People Import Import Resources, Resources, Data Services Data Services Export Export www.ci.anl.gov6 www.ci.uchicago.edu
  7. 7. Workshop Reflections-2• Discussing technology issues in insolation is a recipe for disaster. – Access is closely aligned with other subgroups – It is important to organize in functional units www.ci.anl.gov7 www.ci.uchicago.edu
  8. 8. Workshop Reflections-3• Challenges will continue Social Challenges Changing Requirements/ Changing Technology • Transparency • Openness Adoption Culture • Establishing social ties • Real-time data Adoption is slow • Cross-disciplinary Data Sustainability • High dimensionality Establishing practices • Network bandwidth, Computational resource, Data management constraints www.ci.anl.gov8 www.ci.uchicago.edu
  9. 9. %4 Principles of Data Sharing in EarthCube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 *&/ *-&(!, 44-5-, / 5-, . !*3!*+3. , !$#3% !*+&*!&#, !&(#, and reuse/ $!. % . Lowers the barrier to entry for data sharing&2) !3#$&/ -?, 2!&/ 2!4 / 2, 27 1. % !  Uses tenets like “metadata ASAP” to encourage submission of data !&55, (, #&*-/ $!. 0 &((, #!$#3% ! ) !#, 0 36-/ $!+&#2C &#, !&/ 2!. 34 &#, !36, #+, &2. @ ! 1. *C !P+, !4  Enables creation of “Curation7 3#!&$$#, $&*-3/ !34 !2&*&7 &() . -. 7 !&/ !*33(. !&($3#-*+0among communities, sub-communities Co-ops” . 7 32, (. !&/ 2!0 , *+32. !43#! !0  Serve the NSF !0 , *#-5. !. %5, !*+&*!% , . !530 0 % -*)DMP requirement =-/ $!&/ 2!4 , 2 &5=!*3!. *3#, !&/ 2!1#30 3*, ! . / 5+!&. !#&/ ,  Based on a cloud-based infrastructure to support !0 &#=, *!/ , *C 3#=@, $&*, 2!#, . , &#5+!1#32% !&/ 2!-/ 5#, &. , !*+, !36, #&((!6&(% !34 data discovery, access, and 5*. , !*+, ! !530 1(,mining !*3!*+, ![ &#*+!H5-, / 5, !U3((& 3#&*3#) !6-. -3/ !*+&*!U+#-. !^ ) / / , . 7 0 , / *&#) ! 53((, &$% . !-/ !*+, !I , 2, #&*-3/ !34 &#*+!H5-, / 5, !A 4 , ![ / 3#0 &*-3/ !Y&#*/ , #. !K HA O---!+&6, ! [ YN*-3/ !34 &#*+!. 5-, / 5, !-/ 4 ![ 3#0 &*-3/ !&/ 2!=/ 3C (, 2$, !#, . 3% . ! 3*+!+3#-?3/ *&(() !&/ 2! #5, www.ci.anl.gov&6, !, . *& (-. +, 2!. *#3/ $!53((& 3#&*-3/ ! , *C , , / !*+, !*C 3!&5*-6-*-, . 7 !-((% *#&*, 2! ) !*+, ! 9 !&. . www.ci.uchicago.edu
  10. 10. Enabling A Data Sharing Space: TheDataSpace • Embrace a “semi-­­-structured” notion • Ingest data in raw form, Structuring and refinement of the data and metadata. • Open, extensible architecture that supports Import Software as a Service (SaaS) model, Process for vetting contributed services prior to their incorporation. Based on on-demand resources Resc, • Emphasis on usability instead Services Data DataSpace on developing technology/infrastructure Export & www.ci.anl.gov10 www.ci.uchicago.edu
  11. 11. Post-Charette• 2 Earthcube PI meets at University of Colorado, Boulder – A Concept group meeting, o some representation from Community groups, o July 10, 2012 – A Concept and Community group meeting, o October 4 -5, 2012• Primary objective: Convergence – Through Roadmaps – Architecture – On future steps www.ci.anl.gov11 www.ci.uchicago.edu
  12. 12. Highlights: Summary of Roadmaps• Workplace to collaborate,• Lower barriers for participation,• Openness and extensibility,• Feedback and reproducibility,• Discovery of materials held by long-tailed scientists,• Education and reward system for scientists,• Cross-domain teams and broad collaboration• A new community paradigm. www.ci.anl.gov12 www.ci.uchicago.edu
  13. 13. Defining DataSpace: Architecture-1 Import Resources, Services Data Export www.ci.anl.gov13 www.ci.uchicago.edu
  14. 14. Defining DataSpace: Architecture-2 www.ci.anl.gov14 www.ci.uchicago.edu
  15. 15. Acknowledgements• Don Middleton, NCAR • Dave Fulker, OPeNDAP,• Robert Gibb, New Zealand Landcare • Amarnath Gupta, UCS, Research • Robert Jacob, ANL• Jeff Heard, U. of North Carolina • Chris Jenkins, JPL• Doug Lindholm, U. of Colorado • Craig Mattocks, U. Miami• Joseph Baker, Virginia Tech • Beth Plale, Indiana Univ.• Anne Wilson, U of Colorado • Stephen M. Richard, AZGS• Chris Lynnes, NASA/ESIP Federation • Sameer Sirugeri, Microsoft• Karsten Steinhauser, U. of • Zhangfan Xing, JPL, Minnesota • John Williams, NCAR• Ruth Duerr, NSIDC www.ci.anl.gov15 www.ci.uchicago.edu
  16. 16. Thank You!• Tanu Malik, tanum@ci.uchicago.edu,• Ian Foster, foster@anl.gov• Questions? www.ci.anl.gov16 www.ci.uchicago.edu

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