Skip to content

Creating fingerprint databases and a Bayesian approach to quantify dependencies in evidence

Journal: Online repository of theses and dissertations in the University of Virginia Libraries
Published: 2018
Primary Author: Maria Tackett
Secondary Authors: Under advisement of Dan Spitzner
Research Area: Forensic Statistics

In 2009, the National Research Council issued “Strengthening Forensic Science in the United States: A Path Forward” about the need for more scientific rigor in forensic science. Since then, there has been an effort to make the methods used to analyze forensic evidence more objective, in part through the use of statistics to interpret the evidence. With Lindley (1977) as a guide, this research focuses on two aspects of statistics in forensic science. The first is the creation of large databases that can be used for the development and implementation of statistical methods. We propose a theoretical framework for fully-resourced databases that contain sufficient information to be used for these purposes and demonstrate their use in statistical inference, specifically how the databases can be used to systematically obtain prior information in the Bayesian framework. Recommendations are provided for the type of information that can be included in such databases in the context of fingerprint evidence.

The second aspect is quantifying and interpreting the weight of evidence when multiple candidates are examined as the source of a mark recovered from a crime scene. We propose accounting for the dependencies that exist in the weight of evidence for multiple candidates by imposing a constraint on the set of plausible models, and we examine the properties that exist under this constraint. This research is used to inform guidelines for the examination of multiple candidates identified by a fingerprint matching system such as the Automated Fingerprint Identification System (AFIS).

Related Resources

The q–q Boxplot

The q–q Boxplot

Boxplots have become an extremely popular display of distribution summaries for collections of data, especially when we need to visualize summaries for several collections simultaneously. The whiskers in the boxplot…
The Contribution of Forensic and Expert Evidence to DNA Exoneration Cases: An Interim Report

The Contribution of Forensic and Expert Evidence to DNA Exoneration Cases: An Interim Report

This report is from Simon A. Cole, Vanessa Meterko, Sarah Chu, Glinda Cooper, Jessica Weinstock Paredes, Maurice Possley, and Ken Otterbourg (2022), The Contribution of Forensic and Expert Evidence to…
Likelihood ratios for categorical count data with applications in digital forensics

Likelihood ratios for categorical count data with applications in digital forensics

We consider the forensic context in which the goal is to assess whether two sets of observed data came from the same source or from different sources. In particular, we…
CSAFE Project Update & ASCLD FRC Collaboration

CSAFE Project Update & ASCLD FRC Collaboration

This presentation highlighted CSAFE’s collaboration with the ASCLD FRC Collaboration Hub.