Using Data Science to Improve COVID-19 Response in Developing Countries: Data Visualization
Joshua Blumenstock, Professor
Information, School of
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
The Data-Intensive Development Lab at UC Berkeley (didl.berkeley.edu) is providing data science support to the governments of several Low and Middle Income Countries, as well as humanitarian organizations like GiveDirectly, who are doing their best to effectively respond to the evolving humanitarian crisis caused by the COVID-19 pandemic. So far, we have provided technical support to governments in Afghanistan, Bangladesh, Ghana, Mali, Mexico, Nigeria, Senegal, Sudan, Togo, and Uganda.
The main focus of our current work is on using data science methods (machine learning, computer science, statistics, econometrics, interactive data visualization) to help governments get emergency cash aid to those who need it most. You can read a short article by Prof. Blumenstock about these efforts here: https://www.nature.com/articles/d41586-020-01393-7
Practically, this means we spend a lot of time crunching through large-scale datasets from satellites, mobile phone networks, open street maps, financial institutions, censuses, household surveys, and whatever else is available. Some examples of academic papers related to this work are linked below:
- http://jblumenstock.com/files/papers/jblumenstock_2015_science.pdf
- http://jblumenstock.com/files/papers/jblumenstock_ultra-poor.pdf
- https://web.stanford.edu/~mburke/papers/yeh_et_al_2020.pdf
Role: Interactive and static data visualization / Data Journalism
Apprentices will design and build interactive and static data visualizations that are eye-catching, beautiful, and that effectively communicate complex data analysis to a broad audience. We are looking for students with passion and experience in dataviz. Over the course of the semester, you would be expected to produce outputs along the lines of the following:
- https://www.nytimes.com/interactive/2018/12/10/business/location-data-privacy-apps.html
- https://devseed.com/covid-india-story/
- http://snip.ly/pJsZ#http://www.puffpuffproject.com/languages.html
- https://www.bloomberg.com/graphics/2015-whats-warming-the-world/
Qualifications: All URAP apprentices, irrespective of the specific role or assignment, are expected to be extremely self-motivated, attentive to detail, and meticulous in their approach to data analysis. Apprentices must be able to work independently and be excited to take responsibility and initiative for ensuring their work meets exacting standards of quality.
In your cover letter, please clearly describe your relevant experience, and how you meet the specific qualifications described below. Please include links to your portfolio or examples of work/code that you are proud of and (ideally) that are relevant to the position.
QUALIFICATIONS
● Proficiency in one or more programming languages (required)
● Demonstrated ability to build compelling data visualizations (required - send us examples!)
● Prior experience building interactive data visualizations (preferred)
Day-to-day supervisor for this project: Emily Aiken, Graduate Student
Hours: to be negotiated
Off-Campus Research Site: Zoom (during covid)
Related website: http://didl.berkeley.edu
Related website: http://jblumenstock.com