  This article addresses the problem of formulating efficient and reliable
operational preservation policies that ensure bit-level information integrity
over long periods, and in the presence of a diverse range of real-world
technical, legal, organizational, and economic threats. We develop a
systematic, quantitative prediction framework that combines formal modeling,
discrete-event-based simulation, hierarchical modeling, and then use
empirically calibrated sensitivity analysis to identify effective strategies.
The framework offers flexibility for the modeling of a wide range of
preservation policies and threats. Since this framework is open source and
easily deployed in a cloud computing environment, it can be used to produce
analysis based on independent estimates of scenario-specific costs,
reliability, and risks.
