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Big Data in Policing: Profiling, Patterns, and Out of the Box Thinking

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Trends and Applications in Information Systems and Technologies (WorldCIST 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1365))

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Abstract

Big Data, being a massive amount of data, which requires technologies, information architecture and systems design, and analytical methods, has a significant impact on modern society and the development of security area strategies. This paper investigates the importance of Big Data in policing and discusses the challenges arising from its appliance to maintain public order. It is presented a theoretical study, based on a literature review in the context of policing that allows the establishment of the construct in which the Portuguese National Public Security developed its own Strategic Information System. For the study, some inclusion and exclusion criteria were used to narrow the gaps for a better understanding of the subject. Even though some questions arise from using the Big Data, such as processing, profiling, parsing algorithms that can conduct excessive normalisations of the data, Big Data is leverage in policing and a tool of predictive policing.

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References

  1. Morgado, S.M.A., Moniz, T., Felgueiras, S.: Facebook and polícia de segurança pública: an exploratory study if follower’s engagement. In: Rocha, Á., Reis, J., Peter, M., Bogdanović, Z. (eds.) Marketing and Smart Technologies. Smart Innovation, Systems and Technologies, pp. 363–376. Springer, Cham (2020)

    Google Scholar 

  2. Kahneman, D.: Pensar depressa e devagar. Temas e debates, Lisboa (2002)

    Google Scholar 

  3. Rosling, H., Rönnlund, A., Rosling, O.: Factfulness. Temas e debates, Lisboa (2019)

    Google Scholar 

  4. Dick, P.D.: The Minority Report. Orion Books, London (2005)

    Google Scholar 

  5. Morgado, S.M.A., Anjos, O.: Qualitative methodology helping police sciences: building a model for prevention of road fatalities in São Tomé and Principe. In: Costa, A., Reis, L., Moreira, A. (eds.) Computer Supported Qualitative Research. WCQR 2018. Advances in Intelligent Systems and Computing, vol. 861, pp. 291–304. Springer, Cham (2018)

    Google Scholar 

  6. Pais, L.G.: Predictive policing: Is it really an innovation? In: European Law Enforcement Research Bulletin, Special Conference Edition: Innovations in law enforcement: Implications for practice, education and civil society, (4 SCE), pp. 125–131. CEPOL, Budapeste (2018)

    Google Scholar 

  7. Lohr, S.: The origins of ‘big data’: an etymological detective story. [Bits]. https://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/. Accessed 08 Nov 2020

  8. Laney, D.: 3-D data management: controlling data volume, velociy and variety. META Group. https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf. Accessed 20 Oct 2020

  9. Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D., Tufano, P.: Analytics: The Real-World Use of Big Data. https://www.informationweek.com/pdf_whitepapers/approved/1372892704_analyics_the_real_world_use_of_big_data.pdf. Accessed 20 Oct 2020

  10. Dijcks, J.: Oracle White Paper: Big Data for the Enterprise. Oracle Corporation, Redwood Shores (2013)

    Google Scholar 

  11. Higdon, R., Haynes, W., Stanberry, L., Stewart, E., Yandl, G., Howard, C., Broomall, W., Koller, N., Kolker, E.: Unravelling the complexities of life sciences data. Big Data 1(1), 42–50 (2013)

    Article  Google Scholar 

  12. Intel IT Center: Big data analytics: Intel’s IT manager survey on how organizations are using Big Data. Intel IT Center, Intel Corporation, Santa Clara (2012)

    Google Scholar 

  13. Suthaharan, S.: Big data classification: problems & challenges in network intrusion prediction with machine learning. Perform. Eval. Rev. 41(4), 70–73 (2014)

    Article  Google Scholar 

  14. Beyer, M.A., Laney, D.: The importance of “Big Data”: A definition (Report No. G00235055) (2012)

    Google Scholar 

  15. Zaslavsky, A., Perera, C., Georgakopoulos, D.: Sensing as a service and big data. In: Proceeding of the International Conference on Advances in Cloud Computing (ACC), pp. 21–29. ACC, Bangalore (2013)

    Google Scholar 

  16. Zikopoulos, P., Eaton, C., deRoos, D., Deutsch, T., Lapis, G.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw, New York (2011)

    Google Scholar 

  17. Gebert, G.: What is Big Data?. (Paper presentation). In: Conference on Big Data in Forensic Science. Polícia Judiciária, Lisboa (2014)

    Google Scholar 

  18. De Mauro, A., Greco, M., Grimaldi, M.: A formal definition of big data based on its essential features. Libr. Rev. 65(3), 122–135 (2016)

    Article  Google Scholar 

  19. Coyle, K.: Mass digitization of books. J. Acad. Libr. 32(6), 641–645 (2006)

    Article  Google Scholar 

  20. Somers, J.: Torching the modern-day library of Alexandria. The Atlantic. https://www.theatlantic.com/technology/archive/2017/04/the-tragedy-of-google-books/523320/. Accessed 08 Nov 2020

  21. Mayer-Schönberger, V., Cukier, K.: Big Data: A Revolution That Will Transform How We Live, Work and Think. John Murray, London (2013)

    Google Scholar 

  22. Pereira, M.R.: Big Data: O caso do Sistema Estratégico de Informação, Gestão e Controlo operacional da Polícia de Segurança Pública. (Unpublished Master Thesis). Instituto Superior de Ciências Policiais e Segurança Interna, Lisboa (2016)

    Google Scholar 

  23. Michel, J.B., Shen, Y.K., Aiden, A., Veres, A., Gray, M.K., Pickett, J.P., Hoiberg, D., Clancy, D., Norvig, P., Orwant, J., Pinker, S., Nowak, M.A., Aiden, E.L.: Quantitative analysis of culture using millions of digitized books. Science 331(6014), 176–182 (2011)

    Article  Google Scholar 

  24. Rowley, J.: The wisdom hierarchy: Representations of the DIKW hierarchy. J. Inf. Sci. 33(2), 163–180 (2007)

    Article  Google Scholar 

  25. Jifa, G.: Data, information, knowledge, wisdom and meta-synthesis of wisdom - comment on wisdom global and wisdom cities. Proc. Comput. Sci. 17, 713–719 (2013)

    Article  Google Scholar 

  26. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute, New York (2011)

    Google Scholar 

  27. Dhanklad, S.: A brief summary of apache hadoop: a solution of big data problem and hint comes from Google, towards data science. https://towardsdatascience.com/a-brief-summary-of-apache-hadoop-a-solution-of-big-data-problem-and-hint-comes-from-google-95fd63b83623?fbclid=IwAR2qGnPlGhsgtoW4Za0IgJsD2uFMB5hv4xMLZaouy1OgdNhlPUJdSJyW0b0. Accessed 08 Nov 2020

  28. Xiong, W., Yu, Z., Bei, Z., Zhao, J., Zhang, F., Zou, Y., Xu, C.: A characterization of big data benchmarks. In: Proceedings – 2013 IEEE International Conference on Big Data, Big Data, pp. 118–125. IEEE, Santa Clara (2013)

    Google Scholar 

  29. Moore, G.E.: Cramming more components onto integrated circuits. IEEE Solid-State Circ. Newsl. 11(5), 33–35 (2006)

    Article  Google Scholar 

  30. McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harv. Bus. Rev. 90(10), 61–67 (2012)

    Google Scholar 

  31. Ward, J.S., Barker, A.: Undefined by data: a survey of big data definitions. https://arxiv.org/pdf/1309.5821.pdf. Accessed 12 Dec 2020

  32. Wang, R.Y., Strong, D.M.: Beyond accuracy: what data quality means to data consumers. J. Manage. Inf. Syst. 12(4), 5–33 (1996)

    Article  Google Scholar 

  33. Wang, R.Y., Ziad, M., Lee, Y.W.: Data Quality: Advances in Database Systems. Kluwer Academic Publishers, Dordrecht (2002)

    Google Scholar 

  34. Chen, H., Chiang, R., Storey, V.: Business intelligence and analytics: from big data to big impact. MIS Q. 36(4), 1165–1188 (2012)

    Article  Google Scholar 

  35. Dumbill, E.: Making sense of big data. Big Data 1(1), 1–2 (2013)

    Article  Google Scholar 

  36. Manovich, L.: Trending: the promises and the challenges of big social data. https://manovich.net/content/04-projects/067-trending-the-promises-and-the-challenges-of-big-social-data/64-article-2011.pdf. Accessed 09 Nov 2020

  37. Felgueira, S., Machado, P.: Modelo de diagnóstico de Ordem Pública: uma abordagem metropolitana sincrónica. In: Rollo, M.F., Gomes, P.M., Rodríguez, A.C. (eds.) Polícia (s) e Segurança Pública: História e Perspetivas Contemporâneas, pp. 395–418. MUP, Lisboa (2020)

    Google Scholar 

  38. Bayley, D.H.: The complexities of 21st century policing. Policing: J. Policy Pract. 10(3), 163–170 (2016)

    Article  Google Scholar 

  39. Morgado, S., Mendes, S.: O futuro numa década: Os desafios económicos e securitários de Portugal. Politeia – Revista do Instituto de Ciências Policiais e Segurança Interna Ano X-XI-XII: 2013–2014–2015 (1: Studio varia), pp. 9–35 (2016)

    Google Scholar 

  40. Mendes, S., Morgado, S.: Intelligence services intervention: constraints in Portuguese democratic state. In: Teixeira, N.S., Oliveira, C.S., Lopes, M., Sardinha, B., Santos, A., Macedo, M. (eds.) International Conference on Risks, Security and Citizens: Proceedings/Atas, pp. 285–297. Município de Setúbal, Setúbal (2017)

    Google Scholar 

  41. Felgueiras, S., Pais, L.G., Morgado, S.M.A.: Interoperability: diagnosing a novel assess model. In: European Law Enforcement Research Bulletin, Special Conference Edition: Innovations in law enforcement: Implications for practice, education and civil society, (4 SEC), pp. 1–6. CEPOL, Budapest (2018)

    Google Scholar 

  42. Nagin, D.S., Solow, R.M., Lum, C.: Deterrence, criminal opportunities, and police. Criminology 53(1), 74–100 (2015)

    Article  Google Scholar 

  43. Elias, L.: Desafios e prospetiva. Instituto Superior de Ciências Policiais e Segurança Interna, Lisboa (2018)

    Google Scholar 

  44. Chan, J., Moses, L.B.: Making sense of big data for security. Br. J. Criminol. 57(2), 299–319 (2016)

    Google Scholar 

  45. Crawford, K.: The anxieties of Big Data. The New Inquiry (2014). https://thenewinquiry.com/the-anxieties-of-big-data/. Accessed 20 Oct 2020

  46. Morgado, S.M.A.: Crime and socio-economic context: a framework approach. In: Proceedings in Advanced Research in Scientific Areas (ARSA 2013), pp. 139–142. EDIS, Slovakia (2013)

    Google Scholar 

  47. Babuta, A.: Big data and policing: an assessment of law enforcement requirements, expectations and priorities. Royal United Services Institute for Defence and Security Studies. https://rusi.org/sites/default/files/201709_rusi_big_data_and_policing_babuta_web.pdf. Accessed 13 Nov 2020

  48. Ratcliffe, J.: Intelligence-Led Policing. Routledge, New York (2016)

    Book  Google Scholar 

  49. Ferguson, A.G.: The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. New York University Press, New York (2017)

    Book  Google Scholar 

  50. Speranza, A.: Big data and law enforcement: on predictive policing. Medium. https://medium.com/@alishope/big-data-and-law-enforcement-on-predictive-policing-a16afd882dd2. Accessed 14 Oct 2020

  51. Bovens, M.A.P., Schillemans, T., Goodin, R.E.: Public accountability in MAP. In: Bovens, M.A.P., Goodin, R.E., Schillemans, T. (eds.) The Oxford Handbook of Public Accountability, p. 18. Oxford University Press, Oxford (2014)

    Google Scholar 

  52. Joh, E.E.: Policing by numbers: big data and the fourth amendment. Washington Law Rev. 89(1), 35–68 (2014)

    Google Scholar 

  53. Wyllie, D.: Rise of the crime analyst, PoliceOne. https://www.policeone.com/police-products/software/Data-Information-Sharing-Software/articles/6396540-Rise-of-the-crime-analyst/. Accessed 13 Nov 2020

  54. Richards, N.M., King, J.H.: Three paradoxes of big data. Stanford Law Rev. 66(41), 41–43 (2013)

    Google Scholar 

  55. Chen, H., Yan, Z.: Security and privacy in big data lifetime: a review. In: International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, pp. 3–15. Springer, Cham (2016)

    Google Scholar 

  56. Desai, P.V.: A survey on big data applications and challenges. In: Proceedings of the 2nd International Conference on Inventive Communication and Computational Technologies (ICICCT 2018) IEEE Xplore Compliant, pp. 737–740. Gnanamani College of Technology, Tamilnadu (2018)

    Google Scholar 

  57. Feng, M., Zheng, J., Ren, J., Hussain, A., Li, X., Xi, Y., Liu, Q.: Big data analytics and mining for effective visualization and trends forecasting of crime data. IEEE Access 7, 106111–106123 (2019)

    Article  Google Scholar 

  58. Perry, W.L., McInnis, B., Price, C.C., Smith, S.C., Hollywood, J.S.: Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations. RAND Corporation, Santa Monica (2013)

    Book  Google Scholar 

  59. Pareto, V.: Cours d’économie politique. Libraire Droz, Geneva (1964)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Major Events Laboratory, Research Center (ICPOL), Instituto Superior de Ciências Policiais e Segurança Interna, Lisbon, Portugal

    Sónia M. A. Morgado & Sérgio Felgueiras

Authors
  1. Sónia M. A. Morgado
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  2. Sérgio Felgueiras
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Corresponding author

Correspondence to Sónia M. A. Morgado .

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Editors and Affiliations

  1. ISEG, University of Lisbon, Lisbon, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. Department of Information Sciences, University of Sheffield, Lisbon, Portugal

    Ana Maria Ramalho Correia

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Morgado, S.M.A., Felgueiras, S. (2021). Big Data in Policing: Profiling, Patterns, and Out of the Box Thinking. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies. WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1365. Springer, Cham. https://doi.org/10.1007/978-3-030-72657-7_21

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