Presentation by working group on how to approach building a Global WASH Data Portal

1. Challenge #4
Global WASH Data Portal
Emergency Data Science
York University
5 December, 2018
Toronto, Canada

2. Recap of the Challenge
 Track 16 UNHCR WASH indicators: changing over time, geo-spatial
 Missing Data - 70% urban WASH information (out of camp)
 Interoperability with development data (SDG #6)
 Make resource allocation decisions
 Exportability / compatibility with other platforms
 General information access for broad set of users

3.  Incomplete data (HR changes, out of camp)
 Lack of unified source of data (methodologies)
 Validating existing data (trust and quality / Gov data?)
 Decision-making based on bad data (limited data / good enough?)
 Siloed data, unknown data (data from other sectors logistics /
health)
 Dynamic nature of the problem space (fluid environment)
Problems Identified

4.  Take advantage of data that already exists
 Highlight gaps in existing data
 Improve decision making (prioritise needs)
 Be accessible to all humanitarian actors
Refined Goals
Anti Goals
 Fix the cluster data problem (data quality / unifying data collection)

5. We believe people who are allocating resources
have a problem getting and validating the
information they need to make decisions.
We believe we can help by building the portal with
the following information, to compare both in-camp
and out-of-camp data.
Problem Statement

6. Who are our users
Decision makers (people who have money)
● Good data to efficiently allocate resources, good data, prevent worst case
scenarios
● Behaviors: decisions by committee
What is the least amount of information needed to make
meaningful/impactful decisions?

7. What is the least amount of information
needed to make meaningful/impactful
decisions?
JMP data: joint monitoring program
Latrines
Water
Soap
By site, over time

8. In camp

9. Out of camp

10. Overlap Between In
and Out of Camp

11. MVP:
In Camp
● Demographic data
● UNHCR WASH Data
● By site and over time
Out of camp (sub-municipal)
● Demographic data
● WASH indicators
● By geography
From JMP (2 year data collection
cycles)

12. We will know we are right when:
● # Visitors to the site, repeat visitors
● Positive user feedback

13. Tech Stack

14. Next Steps
 Technical scoping
 Produce a business case for the MVP
 Fund
 Trial
 Refine
 Rollout