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                            Funding & Awards
 Foundational Research into the Quantification of the Value of Forensic Evidence for Complex Evidential Forms arising from Impression and Pattern Evidence
Award Information
Awardee
              South Dakota State University
Award #
              2014-IJ-CX-K088
Funding Category
              Competitive
Location
                    Brookings, SD
Status
              Closed
Funding First Awarded
              2014
Total funding (to date)
              $780,301
Original Solicitation
              NIJ FY 14 Research and Development in Forensic Science for Criminal Justice Purposes
Description of original award (Fiscal Year 2014, $780,301)
As submitted by the proposer:  
The development of quantifiable measures of uncertainty in the conclusions of forensic analyses has resulted in the apparition of several ad-hoc methods for approximating the weight of the evidence (in particular for some that are qualitative in nature, such as pattern evidence). The statistical rigor of these methods, as well as their reliability and accuracy, have not been studied.
In fact, some data and research papers suggest that:
1. Some of these methods do not provide an accurate quantification of the weight of forensic evidence;
2. Their statistical and computational complexity is not well understood;
3. These issues are magnified when handling highly dimensional evidence forms such as pattern evidence.
These issues slow the application of these methods in casework and may result in the mistrust of the forensic and legal communities with respect to the statistical inference of the sources of trace samples.
During this 3-years basic research project, we propose to study the validity, accuracy and computational complexity of methods designed to quantify the weight of complex evidence forms, such as pattern evidence and trace evidence. This project will be divided in four phases:
1. The validity, accuracy and computational complexity of 2 methods for quantifying uncertainty in forensic conclusions will be studied using a toy glass example, where the ground truth weight of evidence is known;
2. Two frameworks for using similarity measures (as a means to reduce the dimension of the problem) in the quantification of the weight of evidence will be developed, and their reliability and accuracy will be studied using our toy example;
3. The two frameworks will be applied to a variety of complex forms of evidence (such as fingerprint, handwriting, toolmark and fiber);
4. The reliability of the frameworks, when applied to these evidence types, will be studied as a function of sample and database size.
This project will deliver several products with broad applications to forensic sciences:
1. A series of recommendations on the computational techniques and datasets size required to ensure the reliability and accuracy of methods for approximating the weight of complex forms of evidence;
2. Two frameworks for quantifying the weight of forensic evidence that can be generalized to any forensic field, where there exists a means to quantify the level of similarity between pairs of samples;
3. A free statistical library (with examples, data and documentation) for the R software package for the interpretation of forensic evidence.
ca/ncf



  
Grant-Funded Publications
        
                      Quantification of the weight of fingerprint evidence using a ROC-based Approximate Bayesian Computation algorithm for model selection
                  Quantification of the weight of fingerprint evidence using a ROC-based Approximate Bayesian Computation algorithm for model selection (correction)
                  A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio
                  Deconvolution of dust mixtures
                  Defence against the modern arts: the curse of statistics-Part II: 'Score-based likelihood ratios'
                  Two-stage approach for the inference of the source of high-dimensional and complex chemical data in forensic science
                  U-statistics for estimating performance metrics in forensic handwriting analysis
                  A ROC-based Approximate Bayesian Computation Algorithm for Model Selection: Application to Fingerprint Comparisons in Forensic Science
                  Communicating forensic evidence: Is it appropriate to report posterior beliefs when DNA evidence is obtained through a database search?
                  Deconvolution of Dust Mixtures by Latent Dirichlet Allocation in Forensic Science
                  Review of Several False Positive Error Rate Estimates for Latent Fingerprint Examination Proposed Based on the 2014 Miami Dade Police Department Study
                  Two-Stage Approach for the Inference of the Source of High-Dimension and Complex Chemical Data in Forensic Science
                  Foundational Research into the Quantification of the Value of Forensic Evidence for Complex Evidential Forms Arising From Impression and Pattern Evidence
                  Building a Unified Statistical Framework for the Forensic Identification of Source Problems
                  Kernel-based Methods for Source Identification Using Very Small Particles From Carpet Fibers
                  The Characterization of Monte Carlo Errors for the Quantification of the Value of Forensic Evidence
                  An Argument Against Presenting Interval Quantifications as a Surrogate for the Value of Evidence

  
Date Created: September 11, 2014
    
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