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Scanning of Open Data for Detection of Emerging Organized Crime Threats—The ePOOLICE Project

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Using Open Data to Detect Organized Crime Threats

Abstract

In fighting organized crime , open data provide an important source for both detecting emerging threats, as well as forecasting future threats. This allows the police to plan their resources and capacity for countering the threats in due time to prevent it or at least to mitigate its effects. A vital part of a system supporting the police analysts for this purpose is an efficient and effective system for scanning the open data providing information about the relevant factors in the environment. This chapter presents the ePOOLICE project, aimed at developing a solution, the “ePOOLICE system”, for such a scanning system. Through a prototype demonstrated with use cases, the project provided a proof of concept of an efficient and effective environmental scanning system as part of the early warning system for discovering emerging, as well as likely future, organized crime threats . Main elements in the solution include a central information and knowledge repository; information and knowledge management, including uncertainty management and traceability support; application methodology involving the analyst user in the loop; information fusion; and a comprehensive analysis of legal and ethical issues in deploying such systems. One of the outcomes from the end-user evaluation of the prototype was the desire to integrate internal data to support not only strategic, but also operational analysis and investigation.

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Notes

  1. 1.

    Chapter “Big Data—Fighting Organized Crime Threats while Preserving Privacy” provides a broader analysis and discussion of the underlying ethical and societal issues in deployment of environmental scanning systems like ePOOLICE.

  2. 2.

    Organized crime groups.

  3. 3.

    Serious and organized crime.

  4. 4.

    TRL 5: Component and/or breadboard validation in relevant environment, and TRL 6: System/subsystem model or prototype demonstration in a relevant environment. For a definition of the Technology Readiness Levels, see Table 2 of Appendix B in Army Draft of TRLs for Software (Graettinger et al. 2002).

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Acknowledgements

Research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 312651.

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Authors and Affiliations

  1. ISDEFE, Madrid, Spain

    Raquel Pastor Pastor

  2. Department of Electronic Systems, Aalborg University, Aalborg, Denmark

    Henrik Legind Larsen

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  1. Raquel Pastor Pastor
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Correspondence to Henrik Legind Larsen .

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Editors and Affiliations

  1. Department of Electronic Systems, Aalborg University Department of Electronic Systems, Esbjerg, Denmark

    Henrik Legind Larsen

  2. Spanish Law Enforcement Agency, Guardia Civil Spanish Law Enforcement Agency, Madrid, Spain

    José María Blanco

  3. Isdefe S.A. , Madrid, Spain

    Raquel Pastor Pastor

  4. Machine Intelligence Institute, Iona College Machine Intelligence Institute, New Rochelle, New York, USA

    Ronald R. Yager

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Pastor, R.P., Larsen, H.L. (2017). Scanning of Open Data for Detection of Emerging Organized Crime Threats—The ePOOLICE Project. In: Larsen, H., Blanco, J., Pastor Pastor, R., Yager, R. (eds) Using Open Data to Detect Organized Crime Threats. Springer, Cham. https://doi.org/10.1007/978-3-319-52703-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-52703-1_3

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