Green Space Data Challenge: Community Safety Winners

Continuing our series of Q&As with the first place winners of each category in the Green Space Data Challenge are Zhaowen Guo, Shuang Wu, Chenyue Cao, and Yiwen Wang, who topped the Community Safety category. Congratulations to this dedicated and talented team!

Community Safety Challenge Category Winner: To Combat Gun Violence, Green the Neighborhood

Zhaowen Guo, Shuang Wu, Chenyue Cao, and Yiwen Wang coordinated across opposite coasts of the United States for their project exploring the relationship between green space and gun violence, which took first place in the Community Safety category of the Green Space Data Challenge.

Zhaowen is a Ph.D. candidate in political science and a statistics consultant at the University of Washington, where she teaches data visualization and introductory statistics. Shuang graduated from the University of Washington with a Ph.D. in urban planning and works in Washington, D.C., for an engineering consulting company as a data scientist. Chenyue is in the second year of earning her master’s degree in public administration at the University of Washington and has done some work in spatial statistics. Yiwen is earning her master’s degree in public policy at Georgetown University and has experience with interviewing, questionnaire design and using qualitative data.

Together, they brought a diverse range of skills and experience to bear on their investigation, which combined their interests in both data science and public policy.

Q: Why did you take on this data challenge?

A: The idea of doing data science for the social good really drew us in. Also, this was a great opportunity for all of us to practice and refine our data skills.

Q: Tell us about your project. What was the problem you wanted to solve and what did you do with the data?

A: We wanted to explore how green space affects gun violence, especially in communities of color that have been marginalized. We started with tree equity scores, plotting the distribution of tree equity scores across the U.S. We realized that Washington, D.C., has a very high tree equity score. And then when we looked at our dependent variable, gunshot exposure, we saw that D.C. also has a high level of gun violence. We wanted to explore the racial dimension as well. When we focused on communities of color, like those in Ward 8, we found disproportionately high levels of gunshot exposure.

Our findings show that, while green space can reduce gunshot exposure, the mitigation effect is very small in communities of color, which are much more affected by high levels of poverty and unemployment. Using data visualization methods, we went deeper to identify which aspects of green space can help reduce gun violence, taking diversity and equity into account.

We did a lot of analysis at the grid level to see whether park size, as well as streetlights, can make a difference in reducing gun violence. It turns out those two variables matter a great deal in communities of color. Easier access to smaller parks — compared to larger ones — can reduce gun violence in those communities. Installing streetlights, especially in areas adjacent to parks, can also reduce the risk of gun violence.

Based on our findings, we made two policy recommendations. First, invest in more neighborhood parks for communities of color to increase access to safe green spaces. Second, install additional streetlights in parks and surrounding areas to improve public safety.

Q: How did you decide on which dataset to use?

A: The Challenge provided access to several green space datasets, including the Tree Equity Score dataset, and then we added datasets for gunshot exposure and streetlights. At first, we wanted to explore the whole U.S., but we narrowed it down to D.C., using data at the census tract level.

Q: What motivated you to focus on this topic area?

A: We were all interested in community safety, and we realized from the beginning that green space is very important. Then we became more interested in the relationship between green space and gun violence and the effect in areas of communities of color. In addition, three of us have lived in Washington, D.C., and we wanted to choose an area that we were familiar with and bring our own experience and knowledge of the city to the project.

Q: How do you envision communities using what you created?

A: We wanted to offer actionable and customizable action recommendations for government and community leaders to take, so we hope that they will use these findings to improve community safety and press public officials to invest in neighborhood parks and more streetlights. But our findings also show that gun violence in communities of color is linked to the economic barriers that residents face, so we need greater investment in education, jobs, and financial aid as well.

Q: What would you like to see happen with your idea/project next?

A: We believe this project has several potential directions. We’d like to reproduce our code and make it publicly available so that everyone can access it. We’d also like to present the project at a public data seminar or conference.