Data visualization improvement
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to recommend potential improvements of data visualization available on the Toronto Police Service’s Public Safety Data Portal (PSDP). Students can choose at least one visualization (map or dashboard) to : 1) Derive insights for the development of new visualizations for PSDP such as analytic dashboards, interactive visual exploration, heat maps that would enhance the “analytics journey” of users 2) Development of mock-up solutions that would expand the usage of data visualization by the public 3) Thorough ability to conduct and recommend ways to visualize analytics and tell a story would be a plus 4) Delivery of a final report and/or presentation of recommendations All maps can be found here: http://data.torontopolice.on.ca/pages/maps All data analytics visualizations can be found here: http://data.torontopolice.on.ca/pages/data-analytics
Insights and recommendations to decrease an MCI
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to examine Major Crime Indicators (MCI) data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP), in order to conduct: 1) Exploratory Analysis of one particular crime type from the MCI dataset (Homicide, Robbery, Assault, Theft Over, Auto Theft, Break & Enter) 2) Insights of main crime tendencies and correlations with demographics, other MCIs, temporal data (time of day, day of week), and other factors 3) Final report and/or presentation of recommendations to decrease the crime rate and enhance crime prevention of the selected MCI *Consideration to be given on the use of text mining of street names and free form notes MCI Data can be found at http://data.torontopolice.on.ca/datasets/mci-2014-to-2019
Data visualization improvement
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to recommend potential improvements of data visualization available on the Toronto Police Service’s Public Safety Data Portal (PSDP). Students can choose at least one visualization (map or dashboard) to : 1) Derive insights for the development of new visualizations for PSDP such as analytic dashboards, interactive visual exploration, heat maps that would enhance the “analytics journey” of users 2) Development of mock-up solutions that would expand the usage of data visualization by the public 3) Thorough ability to conduct and recommend ways to visualize analytics and tell a story would be a plus 4) Delivery of a final report and/or presentation of recommendations All maps can be found here: http://data.torontopolice.on.ca/pages/maps All data analytics visualizations can be found here: http://data.torontopolice.on.ca/pages/data-analytics
How can police enforce covid-19 measures effectively?
One of the challenges faced by law enforcement is to have a clear understanding of COVID-19 related measures in order to enforce them properly. Moreover, the public needs a clear understanding of what measures are currently in place in order to comply. Not all measures are clearly communicated through written media releases.. Many measure announcements have been issued at press conferences and Twitter briefings on behalf of government officials, or in other video formats. As the COVID-19 pandemic continues, government measures and restrictions may have changed over time, rendering any comparison of rates of infection between different jurisdictions and geographies very challenging. The Toronto Police Service (TPS) would like students to research and qualify the government and public health measures put in place by City of Toronto, Government of Ontario, City of New York, State of New York, and federal measures on behalf of Canada and the US. Students can also investigate other cities or states as they see fit (i.e. British Columbia, California), as well as possible correlated crimes leveraging search trends platforms. We ask them to: 1) Review government and public health sources of information for confirmed measures put in place in response to the COVID-19 pandemic. 2) Compare confirmed measures in one jurisdiction/municipality/province/state with others 3) Identify the changes made in policies or measures over time, since the beginning of the pandemic 4) Review of reports in media regarding COVID-19 policy enforcement for accuracy and potential for misinformation a. Recommendations for the public as well as officers to follow in order to work with the best quality information and comply with legislation 5) Prepare a final report and/or presentation of findings with recommendations for future pandemics
Machine Learning applications to understand tendencies in Fatal Collisions
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to identify artificial intelligence and machine learning opportunities for the Fatal Collisions data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP), in order to: 1) Derive insights and patterns, especially among potential relationships between variables, such as demographics, temporal data, impaired driving, DUI, and others 2) Build predictive analytics models 3) Create hot-spot mapping 4) Deliver a final report and/or presentation of findings and recommendations *Consideration to be given on the use of text mining of street names and free form notes Leveraging other open data sets, such as City of Toronto, weather-related data, or others to be identified by students, is recommended. Fatal Collisions and other traffic related data can be found at http://data.torontopolice.on.ca/datasets/fatal-collisions
Can Major Crime Indicators be Predicted?
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to research and develop correlation models for the Homicides and Assault data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP) and a comparable city’s open data portal in Canada or US, in order to conduct: The Service would like students to explore and derive insights from the Major Crime Indicators (MCI) dataset in conjunction with at least one other open data set of their choice, for instance 311, City of Toronto, or other open dataset they find interesting and relevant. Ideally, students would: 1) Derive insights and patterns, especially regarding potential relationships between variables, such as demographics, unemployment rates, period of the day and year, other crimes and socio-economic trends, and the comparison of tendencies between cities 2) Build predictive analytics models 3) Perform hot-spot mapping 4) Deliver a final report and/or presentation of findings and recommendations Potential Open Datasets: https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-present/ijzp-q8t2 https://data.cityofnewyork.us/Public-Safety/NYC-crime/qb7u-rbmr https://www.toronto.ca/city-government/data-research-maps/open-data/
Correlation between Major Crime Indicators and Twitter trends
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to research and develop correlation models for the one of the MCI data sets (Homicide, Robbery, Assault, Theft Over, Auto Theft, Break & Enter) available on the Toronto Police Service’s Public Safety Data Portal (PSDP) and Twitter Streaming API, in order to : 1) Investigate potential relationships between that MCI and historical tweets and trending hashtags 2) Derive insights and patterns 3) Build predictive analytics models 4) Deliver a final presentation and/or report of findings and recommendations MCI Data: http://data.torontopolice.on.ca/pages/major-crime-indicators Homicide Data: http://data.torontopolice.on.ca/datasets/homicide-1
Machine Learning Applications for Break and Enter Data
The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to identify artificial intelligence and machine learning applications for the Break & Enter data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP), in order to: 1) Investigate potential relationships between Break & Enters and other factors, such as temporal data (time of day, day of week), neighbourhood, demographics, tree coverage, etc. 2) Derive insights and patterns 3) Build predictive analytics models 4) Create hot-spot mapping of increasing volume B&E areas within the 140 neighbourhoods and identify commonalities in the premise types 5) Deliver a final report and/or presentation of recommendations Leveraging other open data sets, such as 311, City of Toronto, or others to be identified by students, is recommended. B&E Data can be found at http://data.torontopolice.on.ca/datasets/break-and-enter-2014-to-2019
Gang Prevention PR Campaign - Toronto Police Service
The Gang Prevention Town Hall Meetings are an initiative of the Toronto Police Service geared towards educating local communities on preventing youth gang involvement. Community attendance at these events tend to fluctuate, with the lowest attendance in places with high gang activity. The aim of the Town Halls are: To raise awareness of the Toronto Police Service's gang prevention initiative To provide awareness and education on objective youth gang risk factors that are evidence and academically based To connect the local community with social service agencies to mitigate youth gang risk factors with protective factors To identify and empower community leaders with the tools, networks, and support to foster community success from the inside out To gain insight into perceptions, issues and lived experiences of community members impacted by gangs and gang violence To identify gaps in service to provide optimal policing The outcome of this project should be a Public Relations Campaign that can be implemented immediately, and increase community attendance especially in the areas with high gang activity, and generally to increase public awareness of gang prevention strategies.
Content Creation for Recruitment Campaign
The Toronto Police Service (the Service) is undergoing continuous recruitment efforts to strengthen it's workforce by hiring police constables, special constables, parking enforcement officers, court officers, as well as many civilian roles including data analysts, records management and human resources personnel. The Service would like to create a portfolio of stock imagery, video shorts, and/or other relevant digital content for use on social media and digital recruitment channels. We would like students to create these assets. Students from photography studies, visual arts, film studies, etc. would be well suited to this project.
Toronto Police Service Social Media Strategy
Analyze the current social media strategy of Toronto Police Service, examining growth and reach. Measuring its effectiveness in engaging with the community, and devising recommendations to be implemented.
Gang Prevention Town Hall PR Campaign - Toronto Police Service
The Gang Prevention Town Hall Meetings are an initiative of the Toronto Police Service geared towards educating local communities on preventing youth gang involvement. Community attendance at these events tend to fluctuate, with the lowest attendance in places with high gang activity. The aim of the Town Halls are: To raise awareness of the Toronto Police Service's gang prevention initiative To provide awareness and education on objective youth gang risk factors that are evidence and academically based To connect the local community with social service agencies to mitigate youth gang risk factors with protective factors To identify and empower community leaders with the tools, networks, and support to foster community success from the inside out To gain insight into perceptions, issues and lived experiences of community members impacted by gangs and gang violence To identify gaps in service to provide optimal policing The outcome of this project should be a Public Relations Campaign that can be implemented immediately, and increase community attendance especially in the areas with high gang activity.
Toronto Police Service - Community Engagement Framework
The goal of this project is to deliver a framework that will be used by TPS to successfully engage with new immigrants to the City of Toronto. The project outcome should be centered around how TPS should go about educating new immigrants about its services, the role TPS plays in the community and how policing works in Toronto.
Segmentation & Analytics of Major Crime Indicators Data
Segmentation & Analytics of Major Crime Indicator (MCI) Data Students would examine the MCI data* available on the Toronto Police Service's Public Safety Data Portal (PSDP), in order to conduct: 1) High level review & exploratory analysis re segmentation and data cleaning 2) Hot-spot mapping of high volume MCI areas within the 140 neighborhoods by crime type / rate 3) Presentation of recommendations *Consideration to be given on the use of text mining of street names and free form notes MCI Data can be found @ http://data.torontopolice.on.ca/