Data For Good: Poverty Research Cartagena
This project is an exciting opportunity to work with FEM, a non-profit that aims to address social rights issues among rural communities in Colombia. The team is currently working with the mayor’s office in Cartagena, Colombia to access multiple datasets and data sources to establish who and where the extreme poor in Cartagena live. Her team piloted a smartphone-based collection strategy during IOTA Hurricane and obtained data on 4845 households in a very vulnerable area. The first data science challenge was to wrangle and analyze these data to better characterize the population and their needs. This part of the project was conducted in the Spring and Summer of 2021.
Next step will be to integrate data from multiple databases (on health, pension, census, geospatial, etc.), and to devise a method to validate and georeferentiate the information obtained from these merged data. This will be used to then identify the extreme poor whose needs are not currently met or receiving support, to subsequently identify ways to address their needs.
This is a volunteer opportunity for students to use their skills for the social good.
Faculty Advisor
- Project Director: Ana Maria Gonzalez Forero
- Center/Lab:
- Ana is a Colombian born and based social innovator and founder of FEM (http://www.femcolombia.com/about.html), which supports rural communities organizing for their rights. The non-profit receives additional financial support through her for-profit, Cartagena Insider Tours, a tour operator that operates authentic, off-the-beaten-track experiences that go beyond tourism in many ways, teaching travelers about resilience and cooperation. Ana was part of the 2018 inaugural Obama Scholars cohort at Columbia University and joined the Mayor’s Office in Cartagena, as its International Cooperation Officer afterwards. She is a passionate public speaker about socioeconomic inclusion and finding win-win scenarios where people can work together towards more ethical cities and companies.
Project Timeline
- Earliest starting date: 10/01/21
- End date: 12/15/21
- Number of hours per week of research expected during Fall 2021: ~6
Candidate requirements
- Skill sets: proficiency in R, data processing (including handling/imputation of missing values), data visualization (knowledge of tableau is a plus), ability to wrangle and integrate multiple datasets from different sources, excellent communication skills with team members
- Student eligibility: junior, senior, master’s
- International students on F1 or J1 visa: eligible
- Academic Credit Possible: No