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The Who, Why, How & What By: Laban MacOpiyo, Director & Enrica Porcari, Programme Leader AGCommons ( A gricultural  G eospatial  C ommons)
Why
. Improve incomes and lives of small farmers in Sub-Saharan Africa through location-specific information. MISSION
How we got to AGCommons

The outreach findings ,[object Object],[object Object],[object Object],[object Object],[object Object]
AGCommons evolution ,[object Object],[object Object],[object Object],[object Object],[object Object]
Quick Wins ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Quick Wins ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Location Intelligence  Enables interpretation of complex analytics  –  the power of “where”  to optimize performance
Multiple  Perspectives – Many Sources
 Proprietary and Confidential  AWhere, Inc. April 2008 Institutions and Individuals have much to offer and much to share
What is AGCommons? AGCommons Service Bureau Multi-dimensional Multi-directional AGCommons LBI Platform Remote  Sensing Production Crops type Pest Tracking Project data:  Agriculture example Soils fertility Financial Industrial Agriculture Education Governance Policy Business Sustainable Development Census ,[object Object],[object Object],[object Object],[object Object],[object Object],Economics
“ Interrelationships that might otherwise be difficult to describe or explain are often readily understood when visually presented.” 
 visualization drives the ‘next’ question The map visualization delivers accurate, high-impact information content, enabling decision makers to quickly gain an understanding of the key issues. ,[object Object],[object Object],AGCOMMONS Core Competencies Location Based Intelligence!!!
Location Based Intelligence Multidirectional!
Farmer Facing (Realtime!) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Communication!
Policy, Research Facing (Realtime!)
Policy, Research Facing
M&E - institutional memory, transparency and accountability, move away from data silos! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Accountability Transparency Visibility  Compliance Collaborative Iterative Transformative !
Backend
 AGCommons Service Bureau Data Collection Harmonization,  Management  & Dissemination Project  Visualization Decision  Support Communication & Advocacy M&E Support DS PV, C & A DS/ME
Data Services ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],DS PV, C & A DS/ME
Project Visualization, Communications & Advocacy ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Trial Sites Interactive Map SIBWA  Tailored  Field Maps Map illustrating where the project is working and who is involved in the work.  DS PV, C & A DS/ME
Decision, M&E Support ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Visualizing Changes in  Environmental Indicators Nodes of Growth: Project Design via Spatial Analysis Comparison of modeled rice production with seed dealers DS PV, C & A DS/ME
How
  Principles ,[object Object],[object Object],[object Object],[object Object]
The Real Story

Local Farmers Produces harmonized spatial data for agriculture decisions Produces Droppr as an interface to HarvestChoice data Uses ICT expertise to modify Droppr for the local environment, provides access to localized spatial data. Uses Droppr and AGCommons data to help call center workers  help local farmers
But what is IT? ,[object Object],[object Object],UN CGIAR SOCIAL MEDIA NATIONAL LOCAL PROJECTS Data Sources AGCommons www.agcommonsplatform.com Open Source GIS Google Earth Server GIS Offline Mapping ‘ Geo’SMS Direct API’s Modeling Environment
What is AGCommons? AGCommons Service Bureau Multi-dimensional Multi-directional AGCommons LBI Platform Remote  Sensing Production Crops type Pest Tracking Project data:  Agriculture example Soils fertility Financial Industrial Agriculture Education Governance Policy Business Sustainable Development Census ,[object Object],[object Object],[object Object],[object Object],[object Object],Economics
Africa Agriculture GIS Week ,[object Object],[object Object],[object Object],[object Object],[object Object],Meet the Quick-Wins!

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4. agc aagw+presentation rev7

  • 1. The Who, Why, How & What By: Laban MacOpiyo, Director & Enrica Porcari, Programme Leader AGCommons ( A gricultural G eospatial C ommons)
  • 2. Why
. Improve incomes and lives of small farmers in Sub-Saharan Africa through location-specific information. MISSION
  • 3. How we got to AGCommons

  • 4.
  • 5.
  • 6.
  • 7.
  • 8. Location Intelligence Enables interpretation of complex analytics – the power of “where” to optimize performance
  • 9. Multiple Perspectives – Many Sources
 Proprietary and Confidential AWhere, Inc. April 2008 Institutions and Individuals have much to offer and much to share
  • 10.
  • 11.
  • 12. Location Based Intelligence Multidirectional!
  • 13.
  • 14. Policy, Research Facing (Realtime!)
  • 16.
  • 17. Backend
 AGCommons Service Bureau Data Collection Harmonization, Management & Dissemination Project Visualization Decision Support Communication & Advocacy M&E Support DS PV, C & A DS/ME
  • 18.
  • 19.
  • 20.
  • 21.
  • 23. Local Farmers Produces harmonized spatial data for agriculture decisions Produces Droppr as an interface to HarvestChoice data Uses ICT expertise to modify Droppr for the local environment, provides access to localized spatial data. Uses Droppr and AGCommons data to help call center workers help local farmers
  • 24.
  • 25.
  • 26.

Hinweis der Redaktion

  1. Kenyan farmer Mary relies on her own instincts to decide which crops to plant or when to harvest. A farm’s location greatly affects its chance for success and productivity; Local farmers do not have access to location-specific information about their farm’s area: Soils Climate the best crops the most appropriate farming techniques which markets are offering the most competitive prices Like more than 70 percent of rural Africans who live in poverty, Mary depends on agriculture for her family’s food and livelihood
  2. 2 years of preliminary study Outreach efforts Interviews Partnerships with other relevant organizations
  3. Current data is available but not provided in map or time scales that are relevant to farmers Lack of effective networks and channels to disseminate information to farmers Government agricultural extension programs are challenged Focus on electronic delivery when hard copy maps are adequate Information exists but dissemination channels do not Land tenure issues make it difficult for farmers to invest Many efforts don’t last past project funding no sustainable revenue model
  4. Started as an initiative to harmonize and build on large GIS investments of the BMGF Then outreach efforts shown there is a case for a wider set of services Idea of the Service Bureau
  5. GROADS Road in Ethiopia will be passively mapped and compared against feature extracted data from ASTER imagery Open Street Map is great, we love it. But sometimes organizations like the WFP have a difficult time making critical decisions on data from unknown sources This project will prove the methodology and feasibility of collecting data by NGOs who are already working in these areas All the data will be open and freely available. And that’s why we’ve worked with Open Street Map to encourage them to create ‘Trusted Snapshots’ and translate the UNSDI-T data model into the Open Street Map ‘tagged value’ model. AFRICATS Much of the information on seed networks is not generally available outside the research institutions. Lack of knowledge about WHERE the seeds we’re produced leads to mis-understanding about how to grow and where to grow The information exists but no one has looked to exposing it to the internet This project will bring all that information together and make GeoRSS feeds available to the general public. SIBWA This project is going to acquire some Quick Bird images in rural areas in west Africa. Farmers in most cases have never seen their farms from this perspective. The images will be used to delineate some of the local agricultural areas Them the project team will take the hard copy maps out to the rural areas and explain to farmers what they show. In this project the team will not rely on mobile technology, SMS or on-line maps but will instead just go talk to people.
  6. An Africa-based service bureau providing geospatial information technology services to extend the reach and impact of existing agricultural initiatives A “commons” approach, to create the greatest possible good for the largest number of people A technical platform for sharing information across initiatives Promotes the use of geospatial information technologies for agricultural development Identifies and seeks funding for high-win initiatives
  7. An Africa-based service bureau providing geospatial information technology services to extend the reach and impact of existing agricultural initiatives A “commons” approach, to create the greatest possible good for the largest number of people A technical platform for sharing information across initiatives Promotes the use of geospatial information technologies for agricultural development Identifies and seeks funding for high-win initiatives
  8. Extensive outreach efforts Sealed Strategic partnerships Five “quick win” projects to deliver needed solutions immediately and to validate a variety of concepts focusing on different parts of the agro value-chain and different geospatial technologies
  9. Gates Funds HarvestChoice in part to produce spatial data for agricultural and economic tradoffs HarvestChoice program produces the ‘Droppr’ as a research by product Kencall Needs an application that helps locate callers and identify the local agro-ecologoical zone characteristics, local weather, input dealer maps, etc and partners with AGCommons.. AGCommons uses its IT expertise to help KenCall modify the Droppr for the local environment. KenCall then uses the Droppr to help the call center workers help local farmers.
  10. The user sees the end product and not everything that goes into making it. The sophisticated architecture should drive simple end-user focused solutions.
  11. An Africa-based service bureau providing geospatial information technology services to extend the reach and impact of existing agricultural initiatives A “commons” approach, to create the greatest possible good for the largest number of people A technical platform for sharing information across initiatives Promotes the use of geospatial information technologies for agricultural development Identifies and seeks funding for high-win initiatives