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PEPFAR’s experience with spatial data quality
Moving towards spatial data governance
MEASURE GIS Working Group
June 23, 2016
Nate Heard
Humanitarian Information Unit
U.S. Department of State
PEPFAR’s experience with spatial data quality
 What do we mean by spatial data quality?
 PEPFAR spatial data
 Bad data!
 Writing and implementing spatial data governance policy
2
Data are quality data if they are fit for their intended use
Decimal places and precision
3
decimal
places
degrees
N/S or
E/W at
equator
0 1.0 111.32 km
1 0.1 11.132 km
2 0.01 1.1132 km
3 0.001 111.32 m
4 0.0001 11.132 m
5 0.00001 1.1132 m
PEPFAR spatial data
DATIM: Data for Accountability,
Transparency, and Impact
 Built on DHIS2
 36 national and regional programs
 Subnational unit hierarchies to low
levels (>10,000)
 ~46,000 clinical sites
 Requirement for clinical sites to
have latitude and longitude
 Every place has a unique ID
5
UNCLASSIFIED
PEPFAR-managed Spatial Data: Polygons
6
Côte d’Ivoire and Nigeria: District levels
7
PEPFAR-managed Spatial Data: Points
8
Bad data!
The Democratic Republic of the Congo: three health zone boundary sets
10
Wrong!
11
Facilities with missing “–”
Facilities with Reversed Lat-Long
Facility Outside of District
14
Writing and implementing policy
What is data governance?
The creation and implementation of repeatable and scalable data
management policies, processes, and standards for the effective use of data.
PEPFAR Spatial Data Lifecycle
PEPFAR Spatial Data Lifecycle
• Introduction
• Varieties of spatial data in PEPFAR
• Points- access
• Points: Roles and responsibilities
• Prioritizing geographic coordinates for capture or
improvement
• Capturing geographic coordinates
• Quality checks for geographic coordinates
• Point standards
• Datum
• Spatial metadata in DATIM
• Geographic exactness
• Geographic class
• Mobile clinics
• Updating geographic coordinates in DATIM
• Sensitive spatial data
• Polygons - access
• Polygons: Roles and responsibilities
• Importing polygons into DATIM
• Map clearance and publication
• National Spatial Data Infrastructure integration
• Supporting documentation and metadata
• Data formats
• References
PEPFAR GeoNode
18
GIS Module Maintenance: Points
19
Organisation
Unit Profile
Geographic Exactness and Class
code Name
1 Exact
2 Approximate
Geographic Exactness Geographic Location
code Name
1 Administrative Region
2 Populated Place
3 Structure
4
Other Topographical
Feature
20
GIS Analytics Series – “Geography and Data Quality”
21
Downtown San Jose, Costa Rica
22
A PEPFAR-supported Health Facility in Google Street View
23
Thank you

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PEPFAR’s Experience with Spatial Data Quality: Moving towards spatial data governance

  • 1. PEPFAR’s experience with spatial data quality Moving towards spatial data governance MEASURE GIS Working Group June 23, 2016 Nate Heard Humanitarian Information Unit U.S. Department of State
  • 2. PEPFAR’s experience with spatial data quality  What do we mean by spatial data quality?  PEPFAR spatial data  Bad data!  Writing and implementing spatial data governance policy 2
  • 3. Data are quality data if they are fit for their intended use Decimal places and precision 3 decimal places degrees N/S or E/W at equator 0 1.0 111.32 km 1 0.1 11.132 km 2 0.01 1.1132 km 3 0.001 111.32 m 4 0.0001 11.132 m 5 0.00001 1.1132 m
  • 5. DATIM: Data for Accountability, Transparency, and Impact  Built on DHIS2  36 national and regional programs  Subnational unit hierarchies to low levels (>10,000)  ~46,000 clinical sites  Requirement for clinical sites to have latitude and longitude  Every place has a unique ID 5 UNCLASSIFIED
  • 7. Côte d’Ivoire and Nigeria: District levels 7
  • 10. The Democratic Republic of the Congo: three health zone boundary sets 10
  • 14. Facility Outside of District 14
  • 16. What is data governance? The creation and implementation of repeatable and scalable data management policies, processes, and standards for the effective use of data.
  • 17. PEPFAR Spatial Data Lifecycle PEPFAR Spatial Data Lifecycle • Introduction • Varieties of spatial data in PEPFAR • Points- access • Points: Roles and responsibilities • Prioritizing geographic coordinates for capture or improvement • Capturing geographic coordinates • Quality checks for geographic coordinates • Point standards • Datum • Spatial metadata in DATIM • Geographic exactness • Geographic class • Mobile clinics • Updating geographic coordinates in DATIM • Sensitive spatial data • Polygons - access • Polygons: Roles and responsibilities • Importing polygons into DATIM • Map clearance and publication • National Spatial Data Infrastructure integration • Supporting documentation and metadata • Data formats • References
  • 19. GIS Module Maintenance: Points 19 Organisation Unit Profile
  • 20. Geographic Exactness and Class code Name 1 Exact 2 Approximate Geographic Exactness Geographic Location code Name 1 Administrative Region 2 Populated Place 3 Structure 4 Other Topographical Feature 20
  • 21. GIS Analytics Series – “Geography and Data Quality” 21
  • 22. Downtown San Jose, Costa Rica 22
  • 23. A PEPFAR-supported Health Facility in Google Street View 23