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LIDA Seminar Series 20th October 2016

Category
LIDA Seminar
Date
Date
Thursday 20 October 2016, 3:15pm - 6pm
Location
Leeds Institute for Data Analytics, Level 11, Worsley Building, University of Leeds, Clarendon Way, Leeds, LS2 9NL
Category

The Leeds Institute for Data Analytics is pleased to announce the tenth seminar of the series showcasing data analytics.

For this event we welcome Dr Nick Malleson, Associate Professor in Geographical Information Science, from the School of Geography at the University of Leeds. Dr Malleson will be discussing crime analytics and the role of dynamic simulation models. We also welcome our second speaker Miss Emily Sheard, also from the School of Geography at the University of Leeds. Miss Sheard will discuss data as a risk predictor for temporally-concentrated crime series.

Our main speaker for this event is Professor Kate Bowers, Professor of Security and Crime Science at the University College London. Professor Bowers' talk is titled "Crime science, crime analysis and crime reduction"..

Following the seminar there will be a networking reception with drinks and nibbles.

We look forward to seeing you there.

Agenda

15:15: Registration LIDA reception

15:30: Dr Nick Malleson - Crime Analytics and the Role of Dynamic Simulation Models

15:45: Miss Emily Sheard – Data as a risk predictor for temporally-concentrated crime series

16:00: Prof Kate Bowers – Crime science, crime analysis and crime prevention

Crime science is the application of scientific methods and knowledge from many disciplines to the development of practical and ethical ways to reduce crime. This presentation will give an explanation of the multi-disciplinary nature of crime science and how this has assisted with production of new ideas and research evidence.  It will focus on examples of research that has been undertaken under this paradigm at the Jill Dando Institute of Crime Science. In particular it will give an account of the crime analysis which underpinned the development of predictive mapping methods that can assist the police with resource allocation. It will explain the method behind a very recent development which enables crime prediction algorithms to be applied directly to the street network structure. The final section of the discussion focuses on the degree to which such analysis can assist in achieving crime prevention in practice. This will use evidence from a recent evaluation of a predictive mapping based policing initiative and will demonstrate how using locational GPS data leads us to believe that careful consideration needs to be given to the intensity of treatment (here high visibility patrolling) to avoid implementation failure.

17:00: Refreshments and networking

18:00: Close

Booking now open