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DataONE

Research Data Access & Preservation
21 March 2012

Suzie Allard, Ph.D.
University of Tennessee
DataONE vision and approach
Enable new science and knowledge creation through
universal access to data about life on earth and the
environment that sustains it.
1. Build on existing
   cyberinfrastructure   2. Create new
                            cyberinfrastructure   3. Support communities
                                                     of practice




                                                                           2
                                                                               2
DataONE Cyberinfrastructure
Three major components for a      Member Nodes
flexible, scalable, sustainable   • diverse institutions
                                  Coordinating Nodes
network                           • serve local community
                                  • retain complete metadata
                                  Investigator Toolkit
                                  • provide resources for
                                    catalog
                                    managing their data
                                  • indexing for search
                                  • retain copies of data
                                  • network-wide services
                                  • ensure content
                                    availability (preservation)
                                  • replication services




                                                                  3
Training in all elements of the data life cycle

                                Plan

                   Analyze               Collect
    Kepler




             Integrate                         Assure




                   Discover              Describe

                              Preserve
                                                        4
DataONE Education and Training

Summer Internships
Training at Conferences and Workshops
  • Supercomputing 2011
  • DataONE Implementation Workshop: Publishing data as a
    Member Node
  • Ecological Society of America (ESA)
  • American Geophysical Union (AGU)
Educational Modules
Graduate-level course
  • Summer Institute for Environmental Informatics

                                                            5
On-line Education Modules




                            6
Environmental Information Management (EIM) Institute
Graduate students biology, geology, ecology, or other
environmental sciences, environmental engineering, geography
or science librarianship
Conceptual and practical hands-on
training to effectively
design, manage, analyze, visualize, and
preserve data and information:
• Managing data files
• Creating databases and web portals
• Data analysis and visualization
• Techniques for
   managing, analyzing, and visualizing
   geospatial data

                                                               7
DataONE Team and Sponsors
       • Amber Budden, Roger Dahl, Rebecca                     • Ewa Deelman
         Koskela, Bill Michener, Robert Nahf, Mark
       • Servilla
         Dave Vieglais                                         • Peter Honeyman

       • Suzie Allard, Carol Tenopir, Maribeth                 • Jeff Horsburgh
         Manoff, Kimberley Douglass, Robert
       • Waltz, Bruce Wilson Giri
         John Cobb, Bob Cook,                                  • Robert Sandusky
        Palanismy, Line Pouchard
       • Patricia Cruse, John Kunze                            • Bertram Ludaescher

       • Sky Bristol, Mike Frame, Richard Huffine, Viv         • Peter Buneman
         Hutchison, Jeff Morisette, Jake Weltzin, Lisa Zolly
       • Chris Jones, Stephanie Hampton, Matt                  • Cliff Duke
         Jones
       • Paul Allen, Rick Bonney, Steve Kelling                • Carole Goble

       • Ryan Scherle, Todd Vision                             • Donald Hobern

       • Randy Butler                                          • David DeRoure


                                      LEON LEVY
                                      FOUNDATION                                      8
DataONE Team
               Year 1
                            Year 2




                        Year 3


                                     9
Questions




            10
A Science Use Case

               Diverse bird observations and           Model results
               environmental data from
               300,00 locations in the US      Occurrence of Indigo Bunting (2008)
               integrated and analyzed using
               High Performance Computing
               Resources


Land Cover


                                                 Jan   Ap     Jun   Sep    Dec
                                                       r
Meteorology
                                                 • Examine patterns of
                                                   migration
MODIS –        Spatio-Temporal Exploratory       • Infer how climate
Remote         Model identifies factors            change may affect
sensing data   affecting patterns of               bird migration
               migration


                                                                                     11

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DataOne - Suzie Allard - RDAP12

  • 1. DataONE Research Data Access & Preservation 21 March 2012 Suzie Allard, Ph.D. University of Tennessee
  • 2. DataONE vision and approach Enable new science and knowledge creation through universal access to data about life on earth and the environment that sustains it. 1. Build on existing cyberinfrastructure 2. Create new cyberinfrastructure 3. Support communities of practice 2 2
  • 3. DataONE Cyberinfrastructure Three major components for a Member Nodes flexible, scalable, sustainable • diverse institutions Coordinating Nodes network • serve local community • retain complete metadata Investigator Toolkit • provide resources for catalog managing their data • indexing for search • retain copies of data • network-wide services • ensure content availability (preservation) • replication services 3
  • 4. Training in all elements of the data life cycle Plan Analyze Collect Kepler Integrate Assure Discover Describe Preserve 4
  • 5. DataONE Education and Training Summer Internships Training at Conferences and Workshops • Supercomputing 2011 • DataONE Implementation Workshop: Publishing data as a Member Node • Ecological Society of America (ESA) • American Geophysical Union (AGU) Educational Modules Graduate-level course • Summer Institute for Environmental Informatics 5
  • 7. Environmental Information Management (EIM) Institute Graduate students biology, geology, ecology, or other environmental sciences, environmental engineering, geography or science librarianship Conceptual and practical hands-on training to effectively design, manage, analyze, visualize, and preserve data and information: • Managing data files • Creating databases and web portals • Data analysis and visualization • Techniques for managing, analyzing, and visualizing geospatial data 7
  • 8. DataONE Team and Sponsors • Amber Budden, Roger Dahl, Rebecca • Ewa Deelman Koskela, Bill Michener, Robert Nahf, Mark • Servilla Dave Vieglais • Peter Honeyman • Suzie Allard, Carol Tenopir, Maribeth • Jeff Horsburgh Manoff, Kimberley Douglass, Robert • Waltz, Bruce Wilson Giri John Cobb, Bob Cook, • Robert Sandusky Palanismy, Line Pouchard • Patricia Cruse, John Kunze • Bertram Ludaescher • Sky Bristol, Mike Frame, Richard Huffine, Viv • Peter Buneman Hutchison, Jeff Morisette, Jake Weltzin, Lisa Zolly • Chris Jones, Stephanie Hampton, Matt • Cliff Duke Jones • Paul Allen, Rick Bonney, Steve Kelling • Carole Goble • Ryan Scherle, Todd Vision • Donald Hobern • Randy Butler • David DeRoure LEON LEVY FOUNDATION 8
  • 9. DataONE Team Year 1 Year 2 Year 3 9
  • 10. Questions 10
  • 11. A Science Use Case Diverse bird observations and Model results environmental data from 300,00 locations in the US Occurrence of Indigo Bunting (2008) integrated and analyzed using High Performance Computing Resources Land Cover Jan Ap Jun Sep Dec r Meteorology • Examine patterns of migration MODIS – Spatio-Temporal Exploratory • Infer how climate Remote Model identifies factors change may affect sensing data affecting patterns of bird migration migration 11

Hinweis der Redaktion

  1. The DataONE mission/vision is to “enable new science and knowledge creation through universal access to data about life on earth and the environment that sustains it.” DataONE is based on three precepts. 1. We are leveraging existing infrastructure such as the hundreds of existing data centers and repositories, and the myriad of software tools. 2. We are focusing our efforts on developing new infrastructure that better enables interoperability across data centers and between scientific tools and data resources. [The new cyberinfrastructure being created by DataONE is illustrated on a future slide.] 3. We recognize that the largest challenges are sociocultural in nature, and thus we focus significant attention on engaging and supporting the broader community of stakeholders (e.g. scientists, students, librarians).
  2. DataONE is a federated data network built to improve access to Earth science data, and to support science by: engaging the relevant science, data, and policy communities; facilitating easy, secure, and persistent storage of data; and disseminating integrated and user-friendly tools for data discovery, analysis, visualization, and decision-making. There are three principal components:Member Nodes that include a diverse array of data centers and repositories that are associated with national and international agencies and research networks, universities, libraries, etc.Coordinating Nodes that support data replication across Member Nodes (i.e., data centers) as well as network wide services like 24/7 access to metadata at the CNs, indexing and rapid search and discovery, etc.An Investigator Toolkit that includes tools that are widely used by scientists, The tools are coupled with the DataONE resources so that it is, for example, possible to seamlessly and transparently access data at Member Nodes through the tool of your choice.
  3. Other development activities during years 3-5 will focus on expanding the suite of tools that are available through the Investigator Toolkit. New tool additions will be identified and prioritized by the DataONE Users Group.
  4. Other development activities during years 2-5 will focus on expanding the suite of tools that are available through the Investigator Toolkit. New tool additions will be identified and prioritized by the DataONE Users Group.
  5. This final slide illustrates the initial DataONE partners that have now been involved for over 3 years, since the proposal was conceived. The DataONE Users Group now includes significantly more partners and we expect to grow exponentially over the next five years.
  6. The DataONE team is growing!
  7. The Scientific Exploration, Visualization and Analysis Working Group is an example of a scientific use case. By running through a comprehensive case study, this working group was able to provide specific guidance on the challenges faced when conducting data intensive science. Challenges that were communicated to, and met by, the DataONE core CI team and developers.Science requires: Multiple cooperating extreme scale CI components (EVA/eBird pilot lesson learned)EVA pilot collaborated with TeraGrid (now XSEDE) to use HPC and “schlep” data as part of the workflow50K cpu-core hours (SU’s) last year(supporting SOTB 2011)3M hours allocated this year (Cornell CLO team has optimized code for 3-10X speedup, loosened data transfer bottleneck, so we will under run)Plan for 500 species (3 yr data) runs. Currently: 70/wk for 2011 campaignHPC use 10X 2 years in a row. Data increases as well.Conclusion: success breeds scale