Selecting efficient and reliable preservation strategies: modeling long-term information integrity using large-scale hierarchical discrete event simulation

TL;DR

This paper presents a comprehensive simulation-based framework for designing preservation strategies that ensure long-term data integrity amidst diverse threats, leveraging formal modeling and sensitivity analysis.

Contribution

It introduces an open-source, hierarchical discrete-event simulation framework for evaluating preservation policies under various threats and costs.

Findings

Framework effectively models diverse preservation scenarios

Sensitivity analysis identifies optimal strategies

Open-source deployment facilitates broad adoption

Abstract

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.