Researchers have access to a wealth of breach data which is publicly available (information about organization types (healthcare, finance, education), breach methods (hacking, lost or stolen devices, insider incidents), difference between the date of discovery vs reporting, individuals breached, types of exposed data)). Patterns can be identified over time using this data, for example, finding out which sectors are being targeted repeatedly and which attack vector has become more prevalent allow researchers to hypothesize about where vulnerabilities are increasing. Being able to include a temporal aspect allows researchers to estimate the nature of any delays in reporting, as well as whether the reports toward outbreaks are shortened given any policy change or awareness campaign. The extent of the impact per incident (i.e., number of records lost) can also be used toward modeling the distribution of breach impact sizes and provide some insight as to how big of an incident may become in size. Finally, in conjunction with geographic and regulatory context, the scale of breaches could also be used to predict or forecast which sectors or states are likely to see increased breach frequency, thereby informing deterrence, prioritize regulatory action, and allocation of resources to cybersecurity.