Our original plan was to create five one-page documents, each with a different health indicator mapped alongside World Bank or other health aid projects. These indicators included pregnancies, births, water stress, age structures, and ethnic group distribution; however, inaccessibility to age structure and water stress data limited our analyses in these areas. Most of the data that we used, provided by AidData, was easily displayed on maps and thorough enough for statistical and spatial analysis. The health aid projects, for example, each included at least ten pieces of information including project start date, donor, location, and total funding committed. Some of the data that we pulled from other sources—such as WorldPop’s pregnancy and birth data—integrated seamlessly with the information provided by AidData. Other data, however—such as the water stress data from RiverThreat.net—made it much more difficult to create detailed maps.
- Which areas in Senegal have both high numbers of pregnancies and poor access to water?
- In which regions of Senegal are there a large amount of health projects relative to the amount of people and access to water?
- Which densely populated regions have the highest percentage of young children and elder citizens (two of the populations most susceptible to disease and illness)?
We created three one-page documents using the information that was available to us, but we knew that more complete, though currently unavailable, data would have enhanced our ability to answer more interesting questions.
Access to every possible statistic about a country would obviously be ideal, but this is an impractical wish. So how do we deal with this lack of data? Do we submit to it, or do we stand up to it? For this project, we submitted; we did our very best with the data that was available to us. But it doesn’t always have to be this way! Promoting accessibility and transparency of foreign aid data is a primary goal of IPD, and the necessity of such improvements grew increasingly apparent throughout our project.
By the end of this analysis, I had developed a newfound understanding of the types of problems that any group working with development data must deal with. When is the available data adequate? When do we search for more available data? When do we collect new data? Each research project demands a different answer. However, increased accessibility and transparency of data would address this shortcoming in every case.
Jonathan Walsh is an undergraduate studying biomedical engineering at the University of Texas at Austin.