Litcius/Paper detail

An agenda for addressing bias in conflict data

Erin L. Miller, Roudabeh Kishi, Clionadh Raleigh, Caitriona Dowd

2022Scientific Data29 citationsDOIOpen Access PDF

Abstract

With increased availability of disaggregated conflict event data for analysis, there are new and old concerns about bias. All data have biases, which we define as an inclination, prejudice, or directionality to information. In conflict data, there are often perceptions of damaging bias, and skepticism can emanate from several areas, including confidence in whether data collection procedures create systematic omissions, inflations, or misrepresentations. As curators and analysts of large, popular data projects, we are uniquely aware of biases that are present when collecting and using event data. We contend that it is necessary to advance an open and honest discussion about the responsibilities of all stakeholders in the data ecosystem – collectors, researchers, and those interpreting and applying findings – to thoughtfully and transparently reflect on those biases; use data in good faith; and acknowledge limitations. We therefore posit an agenda for data responsibility considering its collection and critical interpretation.

Topics & Concepts

SkepticismData collectionPrejudice (legal term)Event (particle physics)Open dataInterpretation (philosophy)FaithPerceptionData scienceConfirmation biasPsychologyPolitical sciencePublic relationsSocial psychologyComputer scienceSociologyEpistemologySocial scienceLawNeurosciencePhilosophyProgramming languageQuantum mechanicsPhysicsBayesian Modeling and Causal InferenceConservation, Biodiversity, and Resource ManagementTransboundary Water Resource Management