5 research outputs found

    Helping with inquiries: theory and practice in forensic science

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    This thesis investigates the reasoning practices of forensic scientists, with specific focus on the application of the Bayesian form of probabilistic reasoning to forensic science matters. Facilitated in part by the insights of evidence scholarship, Bayes Theorem has been advocated as an essential resource for the interpretation and evaluation of forensic evidence, and has been used to support the production of specific technologies designed to aid forensic scientists in these processes. In the course of this research I have explored the ways in which Bayesian reasoning can be regarded as a socially constructed collection of practices, despite proposals that it is simply a logical way to reason about evidence. My data are drawn from two case studies. In the first, I demonstrate how the Bayesian algorithms used for the interpretation of complex DNA profiles are themselves elaborately constructed devices necessary for the anchoring of scientific practice to forensic contexts. In the second case study, an investigation of a more generalised framework of forensic investigation known as the Case Assessment and Interpretation (CAI) model, I show how the enactment of Bayesian reasoning is dependent on a series of embodied, experiential and intersubjective knowledge-forming activities. Whilst these practices may seem to be largely independent of theoretical representations of Bayesian reasoning, they are nonetheless necessary to bring the latter into being. This is at least partially due to the ambiguities and liminalities encountered in the process of applying Bayesianism to forensic investigation, and also may result from the heavy informational demands placed on the reasoner. I argue that these practices, or 'forms of Bayes', are necessary in order to negotiate areas of ontological uncertainty. The results of this thesis therefore challenge prevailing conceptions of Bayes Theorem as a universal, immutable signifier, able to be put to work unproblematically in any substantive domain, Instead, I have been able to highlight the diverse range of practices required for 'Bayesian' reasoners to negotiate the sociomaterial contingencies exposed in the process of its application

    A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases

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    PhDData stored in individual autonomous databases often needs to be combined and interrelated. For example, in the Inland Water (IW) environment monitoring domain, the spatial and temporal variation of measurements of different water quality indicators stored in different databases are of interest. Data from multiple data sources is more complex to combine when there is a lack of metadata in a computation forin and when the syntax and semantics of the stored data models are heterogeneous. The main types of information retrieval (IR) requirements are query transparency and data harmonisation for data interoperability and support for multiple user views. A combined Semantic Web based and Agent based distributed system framework has been developed to support the above IR requirements. It has been implemented using the Jena ontology and JADE agent toolkits. The semantic part supports the interoperability of autonomous data sources by merging their intensional data, using a Global-As-View or GAV approach, into a global semantic model, represented in DAML+OIL and in OWL. This is used to mediate between different local database views. The agent part provides the semantic services to import, align and parse semantic metadata instances, to support data mediation and to reason about data mappings during alignment. The framework has applied to support information retrieval, interoperability and multi-lateral viewpoints for four European environmental agency databases. An extended GAV approach has been developed and applied to handle queries that can be reformulated over multiple user views of the stored data. This allows users to retrieve data in a conceptualisation that is better suited to them rather than to have to understand the entire detailed global view conceptualisation. User viewpoints are derived from the global ontology or existing viewpoints of it. This has the advantage that it reduces the number of potential conceptualisations and their associated mappings to be more computationally manageable. Whereas an ad hoc framework based upon conventional distributed programming language and a rule framework could be used to support user views and adaptation to user views, a more formal framework has the benefit in that it can support reasoning about the consistency, equivalence, containment and conflict resolution when traversing data models. A preliminary formulation of the formal model has been undertaken and is based upon extending a Datalog type algebra with hierarchical, attribute and instance value operators. These operators can be applied to support compositional mapping and consistency checking of data views. The multiple viewpoint system was implemented as a Java-based application consisting of two sub-systems, one for viewpoint adaptation and management, the other for query processing and query result adjustment

    Improving User Experience In Information Retrieval Using Semantic Web And Other Technologies

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    The need to find, access and extract information has been the motivation for many different fields of research in the past few years. The fields such as Machine Learning, Question Answering Systems, Semantic Web, etc. each tries to cover parts of the mentioned problem. Each of these fields have introduced many different tools and approaches which in many cases are multi-disciplinary, covering more than one of these fields to provide solution for one or more of them. On the other hand, the expansion of the Web with Web 2.0, gave researchers many new tools to extend approaches to help users extract and find information faster and easier. Currently, the size of e-commerce and online shopping, the extended use of search engines for different purposes and the amount of collaboration for creating content on the Web provides us with different possibilities and challenges which we address some of them here
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