Data innovation project success stories from around the world

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Thanks to the innovative framework and the collaboratives, I now don’t have to travel 10,000 km across the vast DRC to obtain certain datasets.
Christian Shadrack
OSM, Democratic Republic of the Congo

The World Bank’s Trust Fund for Statistical Capacity Building (TFSCB) supports projects that are innovative both in technology and approach and make an ongoing difference to a country’s statistical system. Here are some of the highlights and stories from pilot projects in Malawi and Democratic Republic of Congo (DRC) to build a Data Collaborative to support Sustainable Development Goals (SDGs) on Health and Water, Sanitation, and Hygiene (WASH).

In Malawi, more than 30% of the population are still lacking access to safe drinking water and in DRC, this rises to more than 56% (World Development Indicators, 2017)[1]. The Global SDG 6.1[2] addresses this problem and there are many actors who are actively gathering data in this field; however due to the lack of a mature data ecosystem that can produce data for reporting, oftentimes, the data collections result in a fragmented data landscape.

To address these issues, the TFSCB funded a project from a consortium with the Netherlands Red Cross (NRC)[3], the Malawi Red Cross Society, Red Cross of the Democratic Republic of the Congo, and CartONG[4], to support SDG reporting in Malawi and DRC. In partnership with the Global Partnership for Sustainable Development Data, the Development Data Group at the World Bank supported the project’s operations and monitoring and evaluation.

drone launchOne innovative aspect of this project was the use of drones to gather aerial imagery down to 10 cm resolution for water point detection (SDG 6.1.1[5]) in Malawi. Combining the drone imagery with other sources of geospatial data improves the overall quality of water point data sets by removing inconsistencies and enriching attribute information.

The project developed and evaluated an innovative framework[6] to characterize a data ecosystem in its totality, bringing together both sociological and technical aspects along five dimensions, Data Actors & collaboratives, Data Ecosystem Governance, Data Supply, Data Infrastructure, and Data Demand.

diagram

This project also enabled local communities to determine the transportation time needed to reach health centers in the DRC. Health care providers and recipients sometimes relied on handwritten maps (Figure 1) that were inaccurate before the introduction of these tools (Figure 2). Now Ministry of Health staff have received training in geospatial information systems (GIS) as well as open source mapping tools. The support from the TFSCB offered speed and flexibility that empowered government and agencies operating in the local community to solve the problem.

Handwritten maps
Figure 1. Handwritten maps

 

computer generated maps
Figure 2. Computer generated maps

“The framework developed is very useful for the National Statistics Office (NSO) of Malawi to determine how to enrich the official statistics with open mapping data.”
Mercy Kanyuka headshot
Mercy Kanyuka
Commissioner of Statistics, NSO in Malawi

Additional key lessons learned and applied in the project:

  • The importance of open standards towards increasing collaboration and interoperability
  • The need for participatory approaches in the development of technology and data tools
  • The importance of broad multi-stakeholder engagements and convergence in use of supporting platforms
  • The need for localizing the SDGs to give them contextual relevance and sensitivity
  • The importance of developing technology solutions that enhance the freedom and capabilities of the collaborating communities while remaining accessible
  • The need to find operational uses of the data and methodologies shared for stakeholders, in order to get buy-in in the data sharing process and ensure sustainable update
  • The importance of quality in data collection/collation methods, including at field level, to avoid the “garbage in/garbage out” effect

What’s next?

After this foundational field work, the team is planning to keep supporting the data ecosystem growth in the countries. “As multilateral donors play a large role in developing countries with weak governance, they can enforce data sharing and stimulate harmonization of data collection. We observed large differences in participatory capacity; some actors have high data capacity but limited operational knowledge of how to use data for policy and decision making or the other way around. Therefore, another condition for sustainable success concerns fostering data capacities especially among local actors. There is a need for capabilities to integrate diverse data sources for SDG monitoring as census data is not enough” says Marc van den Homberg, a scientific lead from the consortium. 

 

The Trust Fund for Statistical Capacity Building (TFSCB) is supported by the United Kingdom’s Department for International Development, the Government of Korea, and the Department of Foreign Affairs and Trade of Ireland.

 

[2] By 2030, achieve universal and equitable access to safe and affordable drinking water for all.

[5] 6.1.1 Proportion of population using safely managed drinking water services.

Authors

Sun Hwa Song

Statistical Analyst

Siddhesh Kaushik

Senior Business Solutions Officer

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Eva Benita A Tuzon
February 05, 2020

I believe that in knowledge sharing, capacity development happens through this online conversation. Thank you.