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Geospatial, Open-Source Hosting of Agriculture, Resources and Environmental Data Pilot Project Overview & Lessons Learned. Presented by Thomas Hertel Purdue University Presentation at the GEOSHARE Workshop, Purdue University Wednesday, September 10, 2014.

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Geospatial, Open-Source Hosting of Agriculture, Resources and Environmental DataPilot Project Overview & Lessons Learned

Presented by Thomas Hertel

Purdue University

Presentation at the GEOSHARE Workshop, Purdue University

Wednesday, September 10, 2014

origins of geoshare uk foresight project
Origins of GEOSHARE: UK Foresight Project
  • Sir John Beddington, UK Chief Scientist, initiated a project on “The Future of Sustainable Farming”
  • Modeling teams spent 95% of their time building geospatial data to underpin analyses, leaving:
    • Very little time and resources for modeling and analysis
    • Results which were fundamentally non-comparable
  • Precipitated a UK-funded White Paper (Hertel, Villoria et al., 2010) documenting the limitations of existing time series geospatial data for analyses of food and environment security and proposing GEOSHARE
origins of geoshare pilot project
Origins of GEOSHARE: Pilot Project
  • The 2010 White Paper concluded that, despite the many geospatial efforts underway at the time, there we critical limitations holding back discovery and decision making. In particular, most such data sets:
    • Are regional or national, not global; yet some of the most pressing problems are global in scope
    • The global (and many regional) data sets are one-off & incompatible: causes problems of inconsistency; nearly impossible to resolve at end of data pipeline; compatibility must be designed at outset
    • Present high barriers to entry for those outside the geospatial sciences
  • As a result, UK-DFID, DEFRA and USDA stepped forward to fund a pilot project aimed at demonstrating ‘proof of concept’ which ran from 2012-2014
origins of geoshare pilot project1
Origins of GEOSHARE: Pilot Project
  • Pilot project had several key elements:
    • Data base: begin building interoperable data base for land cover, land use and irrigation for Ghana and India
    • Develop several ‘case studies’ to illustrate the usefulness of these data
    • Review the available cyber-infrastructure for facilitating collaboration
    • Develop a proposal for the design of an institution which could sustain GEOSHARE over the long run and review the stakeholder landscape
geoshare as a collection of nodes pilot project funded activities
GEOSHARE as a Collection of Nodes – Pilot Project funded activities

Navin Ramankutty

U. British Columbia

AgMIP

Community:

Delphine Deryng

Technical lead at Purdue: Carol Song

origins of geoshare pilot project2
Origins of GEOSHARE: Pilot Project
  • Pilot project had several key elements:
    • Data base: begin building interoperable data base for land cover, land use and irrigation for Ghana and India
    • Develop several ‘case studies’ to illustrate the usefulness of these data
    • Review the available cyber-infrastructure for facilitating collaboration
    • Develop a proposal for the design of an institution which could sustain GEOSHARE over the long run and review the stakeholder landscape
  • Extension of the pilot to encompass HUBZero
    • Initial pilot did not include funds for development of cyber-infrastructure
    • However, it became clear that development of workflows were key to engaging scientists and decision makers
    • ILSI Research Foundation stepped forward to fund the development of several such workflows over the past year (along with support from ITAP)
workflows on geoshare hub
Workflows on GEOSHARE HUB

Data

Data Reconciliation

SPAM; Data Fusion

  • Gridded source data on land cover & use, water, poverty and environment - flows into:
  • Data reconciliation ‘models’, e.g. SPAM which produce usable data - for use in
  • Biophysical and economic models (e.g., DSSAT, IMPACT, SIMPLE, GTAP)

Sensitivity of results at final stage determines value of improving quality of source data

Source Data

Land Cover

Land Use

Water

Poverty

Environment

IMPACT

DSSAT

what have we learned
What have we learned?
  • Incentives are key: Not just a matter of $$
  • Centralized funding of decentralized activities is unworkable!
  • Cyber-infrastructure facilitates collaboration and dissemination; incentives are again key
  • Must link to user communities
  • Core activities must have stable, L-T support
  • Success will require achieving critical mass
agenda overview
Agenda Overview
  • Why GEOSHARE? Case studies illustrating the importance of consistent, time series geospatial data on agr, environ and poverty
  • HUBZero in action: Connecting communities and synthesizing data
  • Institutional design of GEOSHARE
  • What role for data endorsement?
  • The future of data fusion