TAILIEUCHUNG - A Bayesian network approach to the database search problem in criminal proceedings

At the other extreme, each disk controller now has tens of mega- bytes of storage and a very capable processor. It is quite feasible to have intelligent disks that offer either database access (SQL or some other non-procedural language) and even web service ac- cess. Moving from a block-oriented disk interface to a file inter- face, and then to a set or service interface has been the goal of database machine advocates. | Biedermann etal. Investigative Genetics 2012 3 16 http content 3 1 16 0 Investigative Genetics RESEARCH Open Access A Bayesian network approach to the database search problem in criminal proceedings Alex Biedermann 1 Joelle Vuille2 and Franco Taroni1 Abstract Background The database search problem that is the strengthening of a case - in terms of probative value -against an individual who is found as a result of a database search has been approached during the last two decades with substantial mathematical analyses accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions that is whether or not a given individual is the source of a crime stain this paper relies on graphical probability models in particular Bayesian networks. This graphical probability modeling approach is used to capture within a single model a series of key variables such as the number of individuals in a database the size of the population of potential crime stain sources and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing representing and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. .

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