Knowing What We Don’t: The Fundamental Problem of Data Quality in Conflict Research—and Methodological Solutions

Abstract

Conflict researchers face an unresolved dilemma: the underlying data are often unreliable. When it comes to covert relationships, killings, and illicit markets that organized violence entails, there are simply more incentives to alter information than to tell it straight. How confident can scholars be that on-the-ground events, rather than strategic or omitted information, drive research findings? Despite the evident need for accurate views into clandestine processes, existing work rarely applies systematic checks to verify the seeming “facts” of conflict. This article proposes a methodological toolkit to fill this gap. A first step develops systematic checks to report numerical credibility scores of source quality and corresponding error estimates. A second leverages data of varied strengths for distinct purposes: high-quality sources to triangulate facts and low-quality data to discern strategic images and mis/disinformation. The article tests these standards against major datasets and integrates the protocols into an interactive Data Evaluation Dashboard available for scholarly and policy use.