Data Science Tools for Crime Investigation, Archival, and Analysis

Crime Tracking System (CTS) aims to facilitate the process by automating data entry, storage, and retrieval using a mobile interface and a database to efficiently store said data. Crime investigation plays a significant role in keeping the modern cities safe. The emergence of the field of data science has opened new doors that have high potential in facilitating the process of criminal investigation. Data science enables criminal investigators to create tangible and quantifiable information on criminal social network profiles then analyzes crime concurrence based on location proximity. Aiming at availing the relevance of integrating data science analysis techniques in the criminal investigation, this study examines the suitability of cluster graphs and geolocation proximity (through heat maps) as two of the data science analysis techniques to facilitate criminal investigation process. On one hand, cluster graph analyses the social network of a suspect and examines its centrality, parallel betweenness and community affiliation. On the other hand, geolocation proximity provides an investigator with previous crime occurrences through the use of the heat map visualizing technique. These concepts are tested by embedding them in a mobile application developed to facilitate investigation process. The findings of this study demonstrate that the integration of data science and investigation activities is feasible and can extend the investigation process beyond the scope of the police profile structured database based on manual interrogation activities. This study ends by concluding the limitations and future research directions.