1. M&E of Programs and the Data Infrastructure: GIS as the Rosetta Stone John Spencer MEASURE Evaluation

2. MEASURE Evaluation is funded by the U.S. Agency for International Development (USAID) through Cooperative Agreement GPO-A-00-03-00003-00 and is implemented by the Carolina Population Center at the University of North Carolina in partnership with Constella Futures International, John Snow, Inc., ORC Macro International, and Tulane University. Visit us online at http://www.cpc.unc.edu/measure.

8. Data

9. Where?

10. Why?

12. Value of Mapping  Provides insight into data  Provides a way to link different data  Strengthens data infrastructure by enforcing data schema standards  Picture worth 1,000 words

13. GIS

14. World in Layers

15. Value of Geography  Maps can be  Decision support tools  Analysis tools  Data display tools  More than just mapping

16. GEOGRAPHY CAN STRENGTHEN THE DATA INFRASTRUCTURE

17. Data Infrastructure  Available data  Systems to support, update and disseminate data

20. GIS as Rosetta Stone  GIS can be a “Rosetta Stone” to link different data sets  Produces maps showing linkages that may not have been made before  STRONGER DATA

21. Geography is key link Population DistrictPopulation North3253 South5621 East8732 West7715 OVC DistrictPopulation North812 South1011 East2709 West1411

22. Geography is key link Population and OVC DistrictPopulationOVC North3253812 South56211011 East87322709 West77151411

23. Geography is key link  Seems obvious  Data needs to have a geographic identifier  Data must have complimentary structure  Don’t necessarily need a GIS – can be done in Access or Excel

24. Geographic Identifiers -0.125140 S 34.754213 E -0.125312 S 34.754180 E

25. Geographic Identifiers  Administrative units  Districts  Province  Ward  Etc.  Village or community name

26. OVC CASE STUDY Nigeria

33. One Tool In the Toolbox

34. Key Steps Implementing GIS  Include Geographic Identifier in Data  Where are things?  Software  ArcGIS  Google Earth

35. Summary  Adding the “where” can help understand the “why”  Geography can act as a “Rosetta Stone” to link different elements of the data infrastructure  GIS/mapping can strengthen data quality by enforcing data schema standards

36. MAPPING FOR THE REST OF US Excel and Google Earth

37. Mapping Challenges  Data  Must be well formed and have a geographic identifier  Software

42. Three shelves of ESRI Manuals and third party materials

48. Excel to Google Earth Macro  MEASURE Evaluation developed tool that allows Excel data to be mapped in Google Earth

49. Target Audience  Decision makers  Data and M&E staff  Anyone with Excel data they’d like to map

50. Not a GIS  Data display tool only  Doesn’t do spatial analysis  Buffering, density estimation, spatial stats, etc.  Can’t manage layers Its niche is: a quick, easy to use tool

51. Advantages over a GIS  Permits quick mapping of data  Excel is widely used  Google Earth is free

52. Disadvantages of macro  Requires internet access  Google Earth lacks cartographic “niceties”  Data needs to be structured in the form that the macro expects  (Could be an advantage)

53. Plans  Available on request now  (Email john_spencer@unc.edu)  “Early Beta”  Soliciting feedback and response  Improvements in Year 1 of Phase III

54. DEMO