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Applications of data science in policing: VeriPol as an investigation support tool

Liberatore, Federico ORCID: https://orcid.org/0000-0001-9900-5108, Quijano-Sanchez, Lara and Camacho-Collados, Miguel 2018. Applications of data science in policing: VeriPol as an investigation support tool. Presented at: CEPOL 2017 Research and Science Conference, Budapest, Hungary, 28-30 November 2017. Published in: Nogala, Detlef, Görgen, Thomas, Jurczak, Justyna, Meszaros, Bence, Neyroud, Peter, Pais, Lucia G. and Vegrichtova, Barbora eds. Innovations in Law Enforcement – Implications for practice, education and civil society. European Law Enforcement Research Bulletin. , vol.No 4 S European Union Agency for Law Enforcement Training (CEPOL), pp. 89-96.

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Abstract

Data Science is an interdisciplinary field involving the development of processes and systems to extract knowledge and understanding from data in different formats and from different sources. Considering the large amount of data generated and managed by public safety agencies, Data Science applications in the police sector are numerous. More important are the advantages that the different applications of Data Science could provide the police on issues such as the optimization of resources, the increase of efficiency and effectiveness, the modernization and its exemplariness when compared with other institutions. In this paper we present different potential applications fields of Data Science for the police. In addition, we focus on the case of VeriPol, a tool for automatic detection of false violent robbery reports, currently under development by the Spanish National Police. In particular, we illustrate a detailed analysis of the results of a recent pilot study aimed at assessing the effectiveness of the tool.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: European Union Agency for Law Enforcement Training (CEPOL)
ISSN: 2599-5855
Date of First Compliant Deposit: 9 October 2020
Date of Acceptance: 16 April 2018
Last Modified: 09 Nov 2022 09:21
URI: https://orca.cardiff.ac.uk/id/eprint/135478

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