Difference between revisions of "Group02 Report"
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==Introduction== | ==Introduction== | ||
| + | Environmental criminology focuses on the relations between crime (including aspects such as victim characteristics and criminality) and spatial and behavioural factors. As crime data becomes increasingly available to the public, geo-spatial and temporal analysis of crime occurrence matures to provide better insights. This increased understanding will potentially contribute to enhanced law enforcement efforts and even urban management. | ||
| + | <br> | ||
| + | In our research, we take a step in this direction by examining how geographic and date-time variables interact with other variables to better understand crime occurrences in the city of Los Angeles (LA). Crime data coupled with population by zip code were obtained from the LA city official data repository for analysis and visualization. The research culminates in an interactive application built on R Shiny that allows a casual user to explore, analyse and model data to derive insights. R is used as the tool of choice in creating the web application due to its rich library of packages for statistical analysis and data visualization. With the data visualizations and intuitive user interface in this application, the user can easily filter and transform crime data to derive the insights he or she requires. R’s status as a free software environment for statistical computing and graphics allows for availability for use by many, which would further encourage the spread of such visual analytics initiatives across more fields. | ||
| + | <br> | ||
| + | This paper provides information on our analytical development efforts for the application and consists of 8 sections. The introduction is followed by the motivation and objectives of this research. Section 3 provides a review on previous works in the field. Section 4 describes the dataset and its preparation for modelling. Section 5 describes the design framework as well as visualization methodologies whereas section 6 provides insights we have derived in the process of the development of the application. Future works are stated in section 7 and finally, an installation and user guide in section 8. | ||
==Motivation and Objectives== | ==Motivation and Objectives== | ||
Revision as of 22:10, 3 December 2017
| Overview | Proposal | Poster | Application | Report |
Contents
Introduction
Environmental criminology focuses on the relations between crime (including aspects such as victim characteristics and criminality) and spatial and behavioural factors. As crime data becomes increasingly available to the public, geo-spatial and temporal analysis of crime occurrence matures to provide better insights. This increased understanding will potentially contribute to enhanced law enforcement efforts and even urban management.
In our research, we take a step in this direction by examining how geographic and date-time variables interact with other variables to better understand crime occurrences in the city of Los Angeles (LA). Crime data coupled with population by zip code were obtained from the LA city official data repository for analysis and visualization. The research culminates in an interactive application built on R Shiny that allows a casual user to explore, analyse and model data to derive insights. R is used as the tool of choice in creating the web application due to its rich library of packages for statistical analysis and data visualization. With the data visualizations and intuitive user interface in this application, the user can easily filter and transform crime data to derive the insights he or she requires. R’s status as a free software environment for statistical computing and graphics allows for availability for use by many, which would further encourage the spread of such visual analytics initiatives across more fields.
This paper provides information on our analytical development efforts for the application and consists of 8 sections. The introduction is followed by the motivation and objectives of this research. Section 3 provides a review on previous works in the field. Section 4 describes the dataset and its preparation for modelling. Section 5 describes the design framework as well as visualization methodologies whereas section 6 provides insights we have derived in the process of the development of the application. Future works are stated in section 7 and finally, an installation and user guide in section 8.
