Event-based data collection involves gathering information related to specific events, including when, why, and how they occurred. For example, gathering data related to human rights violations or data about fatalities due to violence are examples of event-based data. Data may be collected from “convenience samples” such as case files, crowd-sourcing platforms, news accounts, or court records; or from random samples, such as household surveys that collect data on incidents of human rights violations.
The data collected may identify perpetrators, victims, and circumstances in each case, and include other useful information such as timelines, locations, and demographics of those involved. Such data can be analyzed to identify useful patterns and trends, and accordingly develop measures for improvement. Event-based data can also help answer the questions of why an event occurred, or what the statistical predictors are for such events that may occur in the future. Automated analysis and visualization may help reveal trends, though the insights gained may depend largely on the judgment and skills of the researcher.
In the human rights context, event-based data is rarely captured through random sampling, raising the risk of statistical bias. Analysts should carefully consider these issues before choosing a visualization for their data.