Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem*

A template Bayesian network for combining forensic evidence on an item with an uncertain relation to the disputed activities

Most of the forensic evidence evaluations given activity level propositions are centered around an item which is assumed to be linked to an alleged activity. However, the relation between an item of interest and an activity may be contested. This study presents a template Bayesian network (BN) for the evaluation of transfer evidence given activity level propositions considering a dispute about the relation of an item to one or more activities. The template BN includes a set of association propositions that enables the combined evaluation of evidence concerning alleged activities of the suspect and evidence concerning the use of an alleged item in those activities. Since the two types of evidence are often from different forensic disciplines, the BN is especially useful in interdisciplinary casework. Throughout the paper, we use a fictive case example that captures the essence of cases for which the template model can be used. The template BN provides a flexible starting point that can be adapted to specific case situations and supports structured probabilistic reasoning by a forensic scientist.

A collection of idioms for modeling activity level evaluations in forensic science

This paper presents a collection of idioms that is useful for modeling activity level evaluations in forensic science using Bayesian networks. The idioms are categorized into five groups: cause-consequence idioms, narrative idioms, synthesis idioms, hypothesis-conditioning idioms, and evidence-conditioning idioms. Each category represents a specific modeling objective. Furthermore, we support the use of an idiom-based approach and emphasize the relevance of our collection by combining several of the presented idioms to create a more comprehensive template model. This model can be used in cases involving transfer evidence and disputes over the actor and/or activity. Additionally, we cite literature that employs idioms in template models or case-specific models, providing the reader with examples of their use in forensic casework.

The importance of considering common sources of unknown DNA when evaluating findings given activity level propositions

Evaluating forensic biological evidence considering activity level propositions is becoming more prominent around the world. In such evaluations it is common to combine results from multiple items associated with the alleged activities. The results from these items may not be conditionally independent, depending on the mechanism of cell/DNA transfer being considered and it is important that the evaluation takes these dependencies into account. Part of this consideration is to incorporate our understanding of prevalent DNA and of background DNA on objects and people, and how activities can lead to common sources of unknown DNA being deposited on items. We demonstrate a framework for evaluation of DNA evidence in such a scenario using Object-Oriented Bayesian Networks and apply it to a motivating case from South Australia.

Probabilistically determining the cellular source of DNA derived from differential extractions in sexual assault scenarios

Sexual assault cases are the type of case that often produces questions about the cellular source of DNA. In these cases multiple findings of microscopy, DNA profiling and presumptive testing need to be considered when addressing source level propositions. In this work, I consider a line of questioning that has been raised a number of times in the recent past, where in court it was disputed that low levels of sperm seen on a microscope slide were the cellular source of the male DNA profile component generated from the sperm fraction of a differential DNA extraction. I demonstrate how the cell scoring results and DNA profiling results can be considered together, in helping address this source level question through the use of Bayesian Networks.

A Practical Guide for the Formulation of Propositions in the Bayesian Approach to DNA Evidence Interpretation in an Adversarial Environment

The interpretation of complex DNA profiles is facilitated by a Bayesian approach. This approach requires the development of a pair of propositions: one aligned to the prosecution case and one to the defense case. This note explores the issue of proposition setting in an adversarial environment by a series of examples. A set of guidelines generalize how to formulate propositions when there is a single person of interest and when there are multiple individuals of interest. Additional explanations cover how to handle multiple defense propositions, relatives, and the transition from subsource level to activity level propositions. The propositions depend on case information and the allegations of each of the parties. The prosecution proposition is usually known. The authors suggest that a sensible proposition is selected for the defense that is consistent with their stance, if available, and consistent with a realistic defense if their position is not known.

The 'factor of two' issue in mixed DNA profiles

A commonly used idea in forensic fields is known as the 'hierarchy of propositions'. DNA analysts commonly report at the sub-source level in the hierarchy. This means that they simply comment on the probability of the evidence for the given propositions that consider contributors that lead to a DNA profile and not on the source of specific biological components, not the activity that led to the transfer or the offence that is reported to have occurred. However DNA analysts also commonly report at a level even lower than the sub-source level. In this 'sub-sub-source' level only reference comparisons to components of a mixture are reported. The difference between the sub-source level and sub-sub-source level is the difference between comparing an individual to a mixture as a whole, or comparing them to only one component of a mixture. This idea has been expressed in the past as the 'two trace' problem or the 'factor of two' problem. With the advent of expert systems that can provide a measure of weight of evidence in the form of a likelihood ratio (LR) for any mixture, resolvable or not, the distinction between these two levels becomes more important. In this paper we explore how the LR can be constructed to report correctly at the sub-source level, by taking contributor orders and genotype set orders into account. We include worked examples of the LR calculation to help explain this confusing issue.

Fusion of laboratory and textual data for investigative bioforensics

Chemical and biological forensic programs focus on the identification of a threat and acquisition of laboratory measurements to determine how a threat agent may have been produced. However, to generate investigative leads, it might also be useful to identify institutions where the same agent has been produced by the same or a very similar process, since the producer of the agent may have learned methods at a university or similar institution. We have developed a Bayesian network framework that fuses hard and soft data sources to assign probability to production practices. It combines the results of laboratory measurements with an automatic text reader to scan scientific literature and rank institutions that had published papers on the agent of interest in order of the probability that the institution has the capability to generate the sample of interest based on laboratory data. We demonstrate the Bayesian network on an example case from microbial forensics, predicting the methods used to produce Bacillus anthracis spores based on mass spectrometric measurements and identifying institutions that have a history of growing Bacillus spores using the same or highly similar methods. We illustrate that the network model can assign a higher posterior probability than expected by random chance to appropriate institutions when trained using only a small set of manually analyzed documents. This is the first example of an automated methodology to integrate experimental and textual data for the purpose of investigative forensics.