Stefaan Verhulst and Andrew Young for the Inter-American Development Bank: Exchanging Data to Create Public Value Across Latin America and the Caribbean

Hannah Pierce — June 09, 2017

In a new article for the Inter-American Development Bank’s Abierto al público blog, Network chief of research Stefaan Verhulst, Network coordinator Andrew Young, and Prianka Srinivasan discuss data collaboratives, a potential solution to leverage private data for public good. They argue that the cross-sector exchange of data can be particularly beneficial to “humanitarian and anti-poverty efforts, urban planning, natural resource stewardship, health, and disaster management.”

The author start by outlining the types of societal benefits created by data collaboratives in Latin America and the Caribbean, along with examples examples of each:

  • Situational Awareness and Response : For example, BBVA collaborated with UN Global Pulse to produce the Hurricane Odile research project which analyzes the anonymized financial data of BBVA’s clients to measure the resilience of communities following a natural disaster. This research can be used not only to support recovery services after a disaster strikes, but also for researching the adaptability of communities following a natural disaster.
  • Public Service Design and Delivery : For example, Waze’s Connected Citizen’s program uses crowdsourced traffic information to help governments design transportation based on an improved understanding of citizen behavior. During the presidential election, the City of Rio de Janeiro accessed Waze’s traffic reports to better allocate transit management personnel to areas with the most congestion.
  • Knowledge Creation and Transfer : For example, in a cross-sector partnership of public, non-profit and private organizations led by the International Center for Tropical Agriculture (CIAT) and the Colombian Ministry of Agriculture, the web-platform “Clima y Sector Agropecuario Colombiano (CSAC)” provides valuable meteorological data to farmers, along with data on the economics and agronomy of rice cultivation.
  • Prediction and Forecasting : For example, researchers from academic and public organizations in the UK and Brazil use crowdsourced geographic information from social media, combined with real-time environmental data and models, to monitor and create early flood and landslide warnings with a view to improve urban resilience.
  • Impact Assessment and Evaluation : For example, through a data sharing agreement with Facebook, UNICEF analyzes Facebook trends and status updates to track and monitor the impact of their public health campaigns like those launched to combat Zika in Brazilian cities.”

They follow with a few words of caution regarding risks, saying:

“To be sure, data collaboratives do introduce some level of risk across the data lifecycle: gathering dirty data at the collection stage, failures to adequately secure data at the processing or sharing stage, the use of biased algorithms at the analyzing stage, and cumulative impacts at the using stage. The responsible use of private-sector data requires targeted risk mitigation strategies.

Our research suggests that such risks can be overcome through the development and implementation of a coherent data responsibility framework and the empowerment of data stewards in institutions tasked with ensuring responsible decision are made about data usages. To learn more about how to create impactful cross-sector data sharing arrangements to create new public value, the GovLab developed the Designing a Data Collaborative Guide based on what is known in the practitioner and research community. The guide offers a step-by-step approach for unlocking the value of private-sector data, and is currently being tested with institutional partners like UNICEF.”

Read more here