A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions

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Ressource 1Download: Taylor 2018 Template BNs FSIgenetics.pdf (1118.24 [Ko])
State: Public
Version: author
Serval ID
serval:BIB_2ACF595BC6B2
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions
Journal
Forensic Science International: Genetics
Author(s)
Taylor Duncan, Biedermann Alex, Hicks Tacha, Champod Christophe
ISSN
1872-4973
ISSN-L
1872-4973
Publication state
Published
Issued date
03/2018
Peer-reviewed
Oui
Volume
33
Pages
136-146
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bayesian networks (BNs). There is much diversity in the way that BN can be constructed. In this work, we develop a template for BN construction that allows sufficient flexibility to address most cases, but enough commonality and structure that the flow of information in the BN is readily recognised at a glance. We provide seven steps that can be used to construct BNs within this structure and demonstrate how they can be applied, using a case example.

Keywords
Pathology and Forensic Medicine, Genetics, Activity level propositions, Bayesian networks, DNA, Data, Evidence evaluation, Likelihood ratio, Pathology and Forensic Medicine, Genetics
Pubmed
Web of science
Open Access
Yes
Create date
10/01/2018 10:25
Last modification date
20/08/2019 13:10
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