El uso de bases de datos en el análisis de la escena del crimen

Palabras clave: Proceso penal, escena del crimen, investigación, bases de datos, efectividad de la prueba

Resumen

Los problemas de utilizar bases de datos en el análisis de la escena del crimen se deben a los cambios en la estructura del crimen, la adaptación de tecnologías innovadoras a las necesidades de las fuerzas del orden y la protección de los derechos humanos. La complejidad de estos aspectos determina la relevancia del tema. El objetivo del estudio es identificar las peculiaridades del uso de bases de datos en el análisis de la escena del crimen y las perspectivas de mejorar las actividades policiales con vistas a las tendencias delictivas. La investigación utilizó métodos lógicos, comparativos y de previsión. Se reveló que el mecanismo de creación y uso de la base de datos tiene como objetivo el cumplimiento de las tareas de trabajo con huellas en la escena del crimen. La correspondencia de las bases de datos con las necesidades de las actividades de aplicación de la ley se evalúa mediante criterios agrupados en grupos de recursos, organizativos y regulatorios. Las bases de datos prospectivas deberían tener en cuenta las tendencias delictivas. Los últimos métodos de trabajo con huellas son la etapa final de la adaptación de la investigación en el campo de la justicia penal. La novedad académica del estudio consiste en un examen crítico del uso de bases de datos en el análisis de la escena del crimen como un complejo de cuestiones de comunicación e innovaciones en las actividades policiales. El estudio abre perspectivas para el desarrollo de algoritmos unificados de intercambio de información para combatir la delincuencia transnacional.

Descargas

La descarga de datos todavía no está disponible.

Biografía del autor/a

Nataliia Akhtyrska, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Candidate of Legal Sciences, Associate Professor, Department of Criminal Process and Criminalistics, Educational and Scientific Institute of Law, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Olena Kostiuchenko, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Candidate of Legal Sciences, Associate Professor, Head of the Department of Criminal Process and Criminalistics, Educational and Scientific Institute of Law, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Yurii Sereda, Kyiv National Economic University named after Vadym Hetman”, Kyiv, Ukraine.

Candidate of Legal Sciences, Associate Professor, Department of Public and International Law, Educational and Scientific Institute “Law Institute of the Kyiv National Economic University named after Vadym Hetman”, Kyiv, Ukraine.

Anna Vynohradova, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Candidate of Legal Sciences, Associate Professor, Department of Criminal Process and Criminalistics, Educational and Scientific Institute of Law, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Ivan Miroshnykov, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Candidate of Legal Sciences, Associate Professor, Department of Criminal Procedure and Criminalistics, Educational and Scientific Institute of Law, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Citas

Al-dhaqm, A., Razak, S., Othman, S. H., Ngadi, A., Ahmed, M. N., Mohammed, A. A. (2017) Development and validation of a Database Forensic Metamodel (DBFM). PLoS ONE, 12(2), e0170793. https://doi.org/10.1371/journal.pone.0170793

Almazrouei, M. A., Dror, I. E., Morgan, R. M. (2020). Organizational and Human Factors Affecting Forensic Decision-Making: Workplace Stress and Feedback. Journal of Forensic Sciences, 65(6), 1968-1977. https://doi.org/10.1111/1556-4029.14542

Amankwaa, A. O. (2020). Trends in forensic DNA data base: Transnational exchange of DNA data Forensic Sciences Research, 5(1), 8–14. https://doi.org/10.1080/20961790.2019.1565651

Amankwaa, А. О., McCartney, С. (2019). The effectiveness of the UK national DNA database. Forensic Science International: Synergy, 1, 45-55. https://doi.org/10.1016/j.fsisyn.2019.03.004

Amankwaa, A. O., McCartney, C. (2021). The effectiveness of the current use of forensic DNA in criminal investigations in England and Wales. WIREs Forensic Science, 3, e1414. https://doi.org/10.1002/wfs2.1414

Blahuta, R. I., Movchan, A. V. (2020). The latest technologies in the investigation of crimes: the current state and problems of use. Lviv: LDUVS.

Carrera, S., Mitsilegas, V., Stefan, M. (2021). Criminal Justice, Fundamental Rights and the Rule of law in the Digital Age: Report of CEPS and QMUL Task Force. Brussels: Centre for European Policy Studies (CEPS).

Cunha, R. R., Arrabal,C. T., Dantas, M. M., Bassanelli, H. R. (2022). Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration. Forensic Science International, 330, 111100. https://doi.org/10.1016/j.forsciint.2021.111100

De Gruijter, M., Nee, C., de Poot, C. J. (2017). Identification at the crime scene: The sooner, the better? The interpretation of rapid identification information by CSIs at the crime scene. Science & Justice, 57(4), 296-306. https://doi.org/10.1016/j.scijus.2017.03.006

De Moor, S. (2018). Forensic DNA databases as data sources for criminological research. Doctoral thesis submitted to obtain the title Doctor in Criminology. Ghent University

De Roo, R. H. D., de Gruijter, M., de Poot, C. J., Limborgh, J. C. M., van den Hoven, P. (2022). The added value of behavioural information in crime scene investigations. Forensic Science International: Synergy, 5, 100290. https://doi.org/10.1016/j.fsisyn.2022.100290

Dela Rama, J. I. J. R. (2022). Problem Areas in Positive Identification, Alibi and Emerging Role of Forensic Science in the Appreciation of Evidence. UST Law Review, 66(1), 93-131. https://lawreview.ust.edu.ph/problem-areas-in-positive-identification-alibi-and-emerging- role-of-forensic-science-in-the-appreciation-of-evidence/

Fedchak, I. A. (2021). Fundamentals of criminal analysis. Lviv: LDUVS.

Gryshchenko, I., Kruhlov, V., Lypchuk, O., Lomaka, I., Kobets, Yu. (2022). Infrastructural development of smart cities as the background of digital transformation of territorial units. Cuestiones Políticas, 40(73), 233-250. https://doi.org/10.46398/cuestpol.4073.11

Interpol. (2022). Our 19 databases. https://www.interpol.int/How-we-work/Databases

Jakovski, Z., Ajanovska, R. J., Stankov, A., Poposka, V., Bitoljanu, N., Belakaposka, V. (2017). The power of forensic DNA data bases in solving crime cases. Forensic Science International: Genetics Supplement Series, 6, e275-e276. https://doi.org/10.1016/j.fsigss.2017.09.085

Jha, P., Jha, R., Sharma, A. (2019). Behavior Analysis and Crime Prediction using Big Data and Machine Learning. International Journal of Recent Technology and Engineering, 8(1), 461-468. https://www.ijrte.org/wp-content/uploads/papers/v8i1/A3493058119.pdf

Kelty, S. F., Ribaux, O., Robertson, J. (2023). Identifying the critical skillset of top crime scene examiners: Why this matters and why agencies should develop top performers. WIREs Forensic Science, 5(5), e1494. https://doi.org/10.1002/wfs2.1494

Khairul, O., Gina, F. G., Noor, H. H. (2021). Crime Scene Investigation Issues: Present Issues and Future Recommendations. Jurnal Undang-Undang dan Masyarakat, 28, 3-10. https://doi.org./10.17576/juum-2021-28-01

Korzh, V. P. (2018). Inspection of the scene: procedural features, forensic recommendations. Kharkiv: KhNUVS.

Lid´en, M., Almazrouei, M. A. (2023). “Blood, Bucks and Bias”: Reliability and biasability of crime scene investigators’ selection and prioritization of blood traces. Science & Justice, 63, 276–293. https://doi.org/10.1016/j.scijus.2023.01.005

Lisohor, V. H. (2020). The use of innovations during the crime scene investigation. Economics. Finanсes. Law, 5, 30-32. https://doi.org/10.37634/efp.2020.5.5

Oatley, G. O., Chapman, B., Speers, J. (2020). Forensic intelligence and the analytical process. WIREs. Data Mining and Knowledge Discovery, 10(3), e1354. https://doi.org/10.1002/widm.1354

Office UK Government. (2023). Forensic Information Databases annual report 2021 to 2022 (accessible version). Corporate report. Presented to Parliament pursuant to Section 63AB(8) of the Police and Criminal Evidence Act 1984. https://www.gov.uk/government/publications/forensic-information-databases-annual- report-2021-to-2022/forensic-information-databases-annual-report-2021-to-2022-accessible-version

Ospina-Bohorquez´, A., Del Pozo, S., Courtenay, L. A., González-Aguilera, D. (2023). Handheld stereo photogrammetry applied to crime scene analysis. Measurement, 216, 112861. https://doi.org/10.1016/j.measurement.2023.112861

Priakhin, Ye. V. (2022). Forensic means and methods of investigating criminal offenses. Lviv: LDUVS.

Pugh, G. (2008). Doing justice to forensic databases. Medicine, Science and the Law, 48(2), 93- 95. https://doi.org/10.1258/rsmmsl.48.2.93.

Rossy, Q., Ioset, S., Dessimoz, D., Ribaux, O. (2013). Integrating forensic information in a crime intelligence database. Forensic Science International, 230(1-3), 137-46. https://doi.org/10.1016/j.forsciint.2012.10.010

Sahay, K. Вh., Balachander, B., Jagadeesh, B., Kumar, G. A., Kumar, R., Parvathy, L. R. (2022). A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering, 103, 108319. https://doi.org/10.1016/j.compeleceng.2022.108319

Santos, F., Machado, H. (2017) Patterns of exchange of forensic DNA data in the European Union through the Prum system. Science & Justice, 57(4), 307–313. https://doi.org/10.1016/j.scijus.2017.04.001

Senthil, P., Selvakumar, S. (2022). A hybrid deep learning technique based integrated multi-model data fusion for forensic investigation. Journal of Intelligent & Fuzzy Systems, 43(5), 6849-6862. https://doi.org/10.3233/JIFS-221307

Singh, H. N. (2020). Crime Scene Investigation. International Journal of Science and Research, 10(11), 642-648. https://doi.org./10.21275/SR211112005543

Srivastava, A., Harshey, A., Das, T., Kumar, A., Yadav, M. M., Shrivastava, P. (2022). Impact of DNA evidence in criminal justice system: Indian legislative perspectives. Egyptian Journal of Forensic Sciences, 12, 51. https://doi.org/10.1186/s41935-022-00309-y

Tehrani, N. (2023). The role of psychological surveillance in reducing harm and building resilience in police forensic investigators. The Police Journal. https://doi.org/10.1177/0032258X231151996

Turvey, B. E., Freeman, J. (2022). Crime Scene Analysis. In: Turvey, B. E. (Ed.), Criminal Profiling: An Introduction to Behavioral Evidence Analysis (pp. 415-456). Fifth Edition. Elsevier Science.

U.S. Department of Justice. (2023). National Crime Information Systems. https://www.justice.gov/tribal/national-crime-information-systems

Wang, J., Li, Z., Hu, W., Shao, Y., Wang, L., Wu, R., Ma, K., Zou, D., Chen, Y. (2019). Virtual reality and integrated crime scene scanning for immersive and heterogeneous crime scene reconstruction. Forensic Science International, 303, 109943. https://doi.org/10.1016/j.forsciint.2019.109943

Wen, Z., Curran, J. M., Wevers, G. (2023). Shoeprint image retrieval and crime scene shoeprint image linking by using convolutional neural network and normalized cross correlation. Science & Justice, 63(4), 439-450. https://doi.org/10.1016/j.scijus.2023.04.014

Wickenheise, R. A. (2023). Proactive crime scene response optimizes crime investigation. Forensic Science International: Synergy, 6, 100325. https://doi.org/10.1016/j.fsisyn.2023.100325

Yu, S.-H., Thomson, G., Rinaldi, V., Rowland, C., Daeid, N. N. (2023). Development of a Dundee Ground Truth imaging protocol for recording indoor crime scenes to facilitate virtual reality reconstruction. Science & Justice, (63), 238–250. https://doi.org/10.1016/j.scijus.2023.01.001

Zarmsky, S. (2021). Why Seeing Should Not Always Be Believing: Considerations Regarding the Use of Digital Reconstruction Technology in International Law. Journal of International Criminal Justice, 19(1), 213–225. https://doi.org/10.1093/jicj/mqab048
Publicado
2023-12-16
Cómo citar
Akhtyrska, N., Kostiuchenko, O., Sereda, Y., Vynohradova, A., & Miroshnykov, I. (2023). El uso de bases de datos en el análisis de la escena del crimen. Revista De La Universidad Del Zulia, 15(42), 193-209. https://doi.org/10.46925//rdluz.42.11

Artículos más leídos del mismo autor/a