This article presents the Event Data on Conflict and Security dataset (EDACS), discusses the inherent problems of event data and shows how these challenges are met within EDACS.
Based on an event data approach, EDACS contributes to the growing number of novel geo-referenced datasets that allow researchers the identification of causal pathways of violence and the dynamics of (transboundary) violence by spatiotemporal disaggregation. However, the inconsiderate use of any of these datasets will give researchers unjustified confidence in their findings as the pitfalls are many and propagating errors can result in misleading conclusions.
Making a stand for transparency in data collection and coding process to empower analysts to challenge the data, and to avoid cascading errors. In particular, we investigate how the choice of news sources, the handling of geographic precision and the use of auxiliary data can bias event data.
We demonstrate how the EDACS dataset design enables the analyst to deal with these issues by providing a set of variables indicating the news sources, possible sources of bias, and detailed information on geographic precision to allow for flexible usage of the data based on individual analytical requirements.