Abstract
DNA and fingerprint identifications continue to form an integral part of the detection of a wide range of crime types, especially volume crime such as burglary and auto crime. More than ten years ago, researchers first commented on the lack of emphasis on ‘outcome’ (i.e. crime detection) related performance indicators for UK police forces. Since then much work has been carried out, mainly by the Association of Chief Police Officers of England & Wales and the Home Office, to produce a framework of forensic science performance indicators that reflect accurately the contribution made by forensic science to crime detection. In this paper, we consider the data currently being collected by five UK police forces that use popular proprietary computer based data collection systems. The accuracy of the data collection has been analysed using a neural network and has identified collection errors in all five forces. These errors are such that they could adversely affect the accuracy and interpretation of the national collection of forensic science data conducted by the Home Office. We propose using this neural network to check the accuracy of data collection and also to provide a ‘front end’ collator for national forensic science data returns to the Home Office. Such an approach would improve the accuracy of data collection nationally and also provide some reassurance over the consistency of data recording by individual forces.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Touche Ross. Review of scientific support for the police, 3 vols, London: Home Office, 1987.
Police Requirements Support Unit, Scientific Support Team. Recommendations for the performance monitoring of scientific support to the police service, London: Home Office, 1991.
Tilley N, Ford A. Forensic science and criminal investigation. Crime Detection and Prevention Paper 73, London: Home Office, 1996.
McCulloch H. Police use of forensic science. Police Research Series Paper 19, London: Home Office, 1996.
Association of Chief Police Officers & Forensic Science Service. Using Forensic Science Effectively. London: ACPO, 1996.
Sims, C. Output related performance indicators for scientific support. Private communication, 2001.
Her Majesty’s Inspectorate of Constabulary. Under the Microscope. London: ACPO, 2000.
Her Majesty’s Inspectorate of Constabulary. Under the Microscope Refocused. London: ACPO, 2002.
Williams, S. R. The Management Of Crime Scene Examination In Relation To The Investigation Of Burglary And Vehicle Crime. Home Office online report 24/04. London: Home Office, 2004.
Police Standards Unit. Forensic Performance Monitors, London: Home Office, 2006.
Adriaans, P., & Zantinge, D. Data Mining, New York, Addison-Wesley, 1996.
Chapman, P., Clinton, J., Kerber, R., et al. CRISP-DM 1.0 Step-by-step data mining guide, USA: SPSS Inc. CRISPWP-0800, 2000.
Giraud-Carrier, C., Povel, O. Characterising data mining software. Journal of Intelligent Data Analysis 2003; 7(3) pp. 181-192.
Mena, J. Investigative data mining for security and criminal detection, 2003.
Adderley, R., Bond, J.W., Townsley, M. Use of data mining techniques to model crime scene investigator performance 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge UK, 2006.
Adderley, R., Bond, J.W. The effects of deprivation on the time spent examining crime scenes and the recovery of DNA & fingerprints. J. Forensic Sci. 2007 (in print).
Adderley, R., Bond, J.W., Townsley, M. Predicting crime scene attendance. Int. J. Police Science & Management, 2007 (in print).
Home Office. National Policing Plan 2005-2008, London: Home Office, 2004.
Swingler, K. Applying Neural networks; A practical guide. Morgan Kaufman, San Francisco, 1996.
Duda, R.O., Hart, P.E. Pattern analysis and scene analysis. John Wiley, New York, 1971.
Langley, P., Sage, S. Induction of selective Bayesian classifiers, Proceedings 10th Conference on Uncertainty in Artificial Intelligence, Seattle, WA; Morgan Kaufmann, 1994, pp. 339-406.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag London Limited
About this paper
Cite this paper
Adderley, R., Bond, J. (2008). Police Forensic science performance indicators – a new approach to data validation. In: Ellis, R., Allen, T., Petridis, M. (eds) Applications and Innovations in Intelligent Systems XV. SGAI 2007. Springer, London. https://doi.org/10.1007/978-1-84800-086-5_12
Download citation
DOI: https://doi.org/10.1007/978-1-84800-086-5_12
Publisher Name: Springer, London
Print ISBN: 978-1-84800-085-8
Online ISBN: 978-1-84800-086-5
eBook Packages: Computer ScienceComputer Science (R0)