How Conflict Obscures the Need for Aid

Open data is a popular tool for researchers, policymakers and donors to study international aid in a new light. Stakeholders can analyze vast streams of detailed data to examine how effectively aid is targeted and implemented. For example, open data gives researchers an unprecedented capacity to track individual development projects on a subnational level from the funding stage through the implementation process. As a student researcher on IPD’s Conflict and Development Team, I utilize open data, geocoding and mapping software to collect, analyze and visualize data on the relationship between violence and international aid.

Our team’s most recent project sheds light on an obstacle that researchers using open data often face in the quest to enhance aid success. In violence-ridden areas, which are often in most need of aid, a lack of sufficient data inhibits accurate analysis of problems and, subsequently, successful aid targeting. How effective can the open data revolution be in areas still plagued by conflict?  It seems that, while the use of open data can improve subnational aid allocation, a conflict-driven data void obscures the need for aid in crucial areas. Donors that are serious about development should not allow the wealth of open data to distract them from the importance of conflict resolution.

To enhance the existing literature on the relationship between violence, resource wealth and development, IPD’s Conflict Team is using open data to categorize and analyze mineral resource extraction locations and armed conflict in dozens of countries worldwide. Using subnational data provided by the US Geological Survey (USGS), we geocoded thousands of resource extraction locations in dozens of countries. By merging this data with information on rebel groups and armed conflict locations from the Armed Conflict Location & Event Data Project (ACLED) dataset, we sought to understand the nature of civil conflict onset and duration in resource-rich locations. While we have made progress using this open data, a thorough subnational analysis is hindered by the very conflict events that we seek to understand.  Nowhere is this paradox more pronounced than in the case of the Democratic Republic of the Congo (DRC).

So far, we have geocoded resource locations in the DRC from 2003-2010. As we compiled datasets of resources and extraction locations, we assigned each location a precision code. These codes establish how precisely we can locate the given extraction point: 1=mine/production facility; 2=nearby city; 3=district level; 4=province level. We always aim for the most precise location information and consult numerous sources, including media reports and government data, to try and pinpoint the exact location. Yet, despite our best efforts, mines and production facilities in the Sud Kivu province of the DRC have proved impossible to track down. Most receive a precision code of 4, diminishing these data points’ analytical value.

Last year, I came across an article in the Washington Post that shed light on the data void in Sud Kivu. Most of Sud Kivu’s mines are located in the Shabunda territory, which is nearly the size of Belgium and largely controlled by a ruthless militia. In the words of the province Minister of Mines, the government “can’t go there.” Thoroughly isolated in the country’s east, the territory has no telephones, no postal service and no radio. A few landing strips serve as the region’s connection to the outside world. While Shabunda is rich in natural resources, extraction is dominated by the Great Lakes Mining Company, an operation run by a rebel group. The rebels who exploit the resources in Shabunda benefit from the territory’s remoteness and lack of development; they stockpile riches in secret while the government and external actors stay away. Due to the volatility in the area, only one international NGO, Médecins Sans Frontiéres, still operates. Yet, astonishingly, Shabunda is home to more than one million Congolese.

These million people face devastating levels of hunger and malnutrition, as rebel violence has destroyed agriculture, fisheries and livestock, which in turn has destroyed jobs and livelihoods. Measles and smallpox have reappeared. Widespread rape by rebels has led to high rates of HIV infection. Over 95% of children lack access to education. A million people, whose fate is largely in the hands of a few violent rebel militias, are stranded in a dire humanitarian crisis mostly unknown to the outside world.

Of course, many researchers and policymakers are aware that the DRC has long been mired in violent conflict. Yet, for those invested in the conflict’s resolution, a complete lack of data on one of the nation’s worst-suffering territories is an incredible hindrance to progress. This example simply reinforces the initial argument that without sufficient data in conflict areas, targeted assistance cannot be effective. Sadly, collecting sufficient data may be impossible in areas where rebel groups benefit from the cover of endless violence.

Our efforts to geocode and map thousands of resource and conflict event locations have already yielded significant inferences into the relationships between resource wealth and violence. Our data visualizations will provide donors and policymakers with evidence of how rebel activity can stunt development in areas that are resource rich. However, a lack of precise data on one area in the DRC offers an equally significant finding: without conflict resolution in key locations, the open data revolution is incomplete.

Blog post by Anna Scanlon, undergraduate at UT Austin majoring in International Relations and Government. 
Map by Amy Leung, who is finishing up her BA in Geography and Sociology at UT Austin.

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