Latin America and the Caribbean (LAC)
In partnership with the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), DPA offered a series of workshops particularly focused on Big Data and the Digital Economy in the Latin American and the Caribbean region designed for development practitioners, policymakers, and researchers. Five editions were delivered in: Santiago de Chile (March 2016), São Paulo (September 2017) —in partnership with Cetic.br—, Mexico City (October 2017) —in collaboration with the National Digital Strategy (EDN) program and the MIT Sloan School of Management—, Santo Domingo (April 2019), and Bogotá (May 2019) —in partnership with DANE.
EmpoderaData builds upon the success of the “Quantitative Step” (Q-Step) program, which was developed as a strategic response to the shortage of quantitatively-skilled social science graduates in the United Kingdom. Together, University of Manchester and Data-Pop Alliance expanded upon the program’s excellent results, exploring this model in the Global South as the “EmpoderaData Project”. The project aimed to promote a virtuous cycle of social transformation by fostering data literacy skills applied to addressing our society’s most pressing issues in the framework of the Sustainable Development Goals (SDGs).
This Thematic Cycle, a joint effort between Eureka and DPA, focused on addiction, disinformation, and violence stemming from social media in the context of Latin America. The Cycle featured two documentaries, a fiction movie, and a book related to the topic that addressed questions such as, Does monetization imply addition? How is social media used to spread hatred and violence? What is surveillance capitalism, and how does it relate to the business model of Internet platforms? The Cycle concluded with a panel discussion led by Paula Villarreal (Data Scientist & Full Stack Engineer), Matías González (Observatorio Legislativo del CELE), and Julie Ricard (Eureka Founder), and moderated by Ivette Yáñez (DPA).
“Parallel Worlds” is a project developed by the Data-Pop Alliance and Oxfam México, with the purpose to analyze inequality in Mexico City, using mobility data provided by Cuebiq’s Data for Good program. The project aimed to inform and influence public policy actors in making decisions that contribute to reducing social and economic segregation based on the privilege and marginalization associated with certain spaces in the city. More specifically, DPA analyzed urban inequality in Mexico City through the mapping of movement patterns in the city, using mobile data to identify segregation patterns, in terms of where people live, work, and consume. The report analyzes three dimensions of inequality: i) in access to education, ii) the right to the city, by analyzing exclusive spaces, and iii) in access to culture. A version of this paper was published in English by Projections, the Journal of the MIT Department of Urban Studies and Planning.
DPA is developing a “Racial Justice Data Project” that will provide a transcontinental view of racial inequality and injustice through the collection of both qualitative and quantitative data from a wide variety of traditional and non-traditional sources (including existing datasets, reports from civil society organizations, legal documents, and social media) to present a fuller picture of the effects of racism in an accessible and actionable manner. The resulting indicators and insights will aim to advance policy, advocacy and awareness raising efforts by civil society associations and policymakers to address structural racism and inequalities in selected countries, including where such data are not collected. The project will: 1) monitor racial violence and inequalities within and across countries in Latin America and the Caribbean and Europe, 2) document demands for racial justice in those regions; 3) highlight institutional actions taken to address these issues; and 4) fill gaps in state-collected data related to racial disparities and violence.
In partnership with Prosperia (Lead) and with support from the Inter-American Development Bank (IDB), this project aims to create both preventive and responsive social protection systems against climate shocks and natural disasters in four Latin American countries: Barbados, Colombia, Honduras and Uruguay. An analysis of pertinent data sources will be conducted, followed by the development of a plan to access these data. Data science models will be built based on a strong methodological approach consisting of five modules: 1) population mapping, 2) analysis of socioeconomic and material vulnerabilities, 3) segmentation of the territories according to their ex-ante risk to climate change shocks and natural disasters, 4) incidence or intensity mapping of the ex-post risk, and 5) development of the preventive and responsive social protection systems.
Criteria, a project led by Prosperia with funding from the Inter-American Development Bank (IDB) and support from Data-Pop Alliance, is an interactive decision support system that empowers policy-makers to explore, analyze, and take decisions on the basis of a large number of potential designs and targeting schemes for social policies. Criteria uses microsimulations on survey and administrative data to visualize the expected poverty impact of policy alternatives resulting from the COVID-19 pandemic, as well as their associated costs.
Four research papers were developed in collaboration with and funded by the French Development Agency (AFD) between 2016 and 2019 under a joint program with Data-Pop Alliance and research partners (Cloud to Street, Flowminder, Harvard Humanitarian Initiative, MIT Media Lab) titled “Strengthening the evidence-base for leveraging Big Data to address global development challenges”. This research program and papers were designed with the following objectives and criteria in mind: to focus on various development challenges in different local contexts in order to ensure relevance; to work with trusted partners, so as to ensure academic quality; and to both reflect and promote key determinants of sustainable development, including smoother, fairer and safer access to data and stronger links between analysts, local decision-makers, and communities. Individually, these papers outlined specific cases and examples of how computational analysis of behavioral data (combined with other datasets) can paint a finer-grained, more complex and dynamic picture of human reality than ‘traditional’ data allows. Collectively, they sketched the contours of a world where public decisions, in the form of policies and programs, may someday be designed, implemented, and evaluated using the best available data and approaches.
This project, developed with the support of the Spanish Agency for International Development Cooperation (AECID), aims to strengthen the technical capacities of government officials in LAC to leverage Big Data for sustainable development and official statistics. During the project’s first phase, the project sought to explain the panorama of Big Data and sustainable development in LAC, focusing on the applicability of sources to obtain statistical information related to issues such as poverty reduction, migration, and climate change. The training phase, based on the report stemming from the first phase, consists of 4 workshops (Big Data for Sustainable Development, Big Data and Poverty, Big Data and Health, Big Data and Security) to be held throughout 2022 and early 2023. These will focus on the applicability of non-traditional and traditional data sources and the applications of different data analysis tools —such as satellite imagery, movement range maps and surveys— to analyze and create projects to achieve the SDGs.
This project aimed to support the IDB (Inter-American Development Bank) in the preparation of the IDB Andean Summit event (November 29, 2018) in Quito, Ecuador. A study was generated identifying new Big Data tools that are being developed and/or used by academic institutions, international organizations, public or private sector that would concretely benefit current and future IDB projects. Based on DPA’s experience, the consultancy’s goal was to contribute to the IDB’s knowledge, identification and capabilities on available technological tools that provide observable material improvements at different stages of current or future projects. The study was based on IDB projects in 5 countries in the region.
This project, developed with support from UNIDAS and GIZ Data Lab, leveraged traditional and non-traditional data sources to assess the reporting capability of women and girls in Mexico City, Bogota and Sao Paulo. The analytical model estimated the probability of registering domestic violence at the locality or municipal level, taking into account personal (e.g. age, educational attainment) and environmental factors (e.g. access to support services, human mobility during the COVID-19 quarantine). The report for Mexico is not available.
Female and male commuters utilize public transport differently, and yet, not enough is known about women commuters’ experiences and challenges. In countries such as Mexico and Peru, gendered perspectives in public policy are starting to be considered, but public action remains insufficient. Together with the socially-focused company WhereIsMyTransport and Rumbo, DPA collected data via online surveys that reflects the issues faced by women transportation users in Mexico City, Mexico, and Lima, Peru. The resulting paper highlights the findings across four areas of interest, and offers actionable recommendations to empower female commuters and promote gender equality.