Meet The Interns (part 1)

This summer, D3 is privileged to partner with the Max M. and Marjorie S. Fisher Foundation and the Next Gen Board to pilot an innovative, community-based internship program. Each intern is working on a community-focused project of their own design, proposed to the D3 team during a highly competitive application process. In addition, each intern is receiving mentorship and professional development under the program.

At D3, we’re tremendously excited about this program, and we wanted to take the opportunity to highlight the five fantastic individuals who are participating! In this post, we’ll be introducing our three Data Analysis Interns – Alexis Farmer, Ayana Rubio, and Sabiha Zainulbhai. Be sure to look out for another post tomorrow, when we’ll introduce Lucas Munson, our Marketing/Outreach Intern, and Jessica Waligora, our Web Development Intern.

What is your history with Detroit? What caused you to pursue this internship?


Alexis: I was born and raised in the city of Detroit. I grew up on the west side of Detroit, and I currently live downtown. I decided to pursue an internship with Data Driven Detroit to continue a project I helped launch as an intern at The White House. I was able to help plan and launch The White House’s Police Data Initiative, which aims to increase transparency and accountability in police departments to improve police-community relations. Through my White House work, I realized that Detroit needs to be a part of this initiative, and Data Driven Detroit is a vehicle that can ensure the necessary data is up-to-date, comprehensible, and stored in one central location for ease of access. I also want to gain some concrete data analytics skills that will help me create my own evidence to support the policy initiatives in my advocacy work.

Ayana: At the DPS elementary school attended by members of my home, and where I volunteer afterschool with a STEM skills club, 23.8% of students have tested with high lead blood levels.

I pursued this internship because Detroit cannot succeed from the neighborhoods-up with unsafe housing and an epidemic of lead-poisoned children. I want to put data in the hands of the 48% of Detroiters living in rented homes & those whose families, neighbors, and loved ones are impacted by poorly regulated safety standards in the face of rising rents.

Sabiha: Prior to starting a Master’s of Public Policy program at the University of Michigan in the Fall of 2014, I had never been to Michigan. Shortly after arriving in Ann Arbor, a concert at a music venue in Detroit’s Cass Corridor brought me to the city. I was intrigued by Detroit’s historic buildings, grand boulevards, and distinct neighborhoods, and was interested in exploring further. And so I did. Throughout the school year, I visited Detroit frequently, and quickly discovered my favorite Detroit destinations.

My interest in Detroit went beyond merely being a tourist a couple of days a month. I was curious about challenges the city faces, and wanted to understand them firsthand, not from widely circulated news stories. At that discovery stage, I was curious what initiatives were happening at the community level and what people who had been living in Detroit were doing to see that their city grew. Lastly, I wanted to learn the tools that would allow me to explore the city in systematic and analytical ways—like GIS.

Tell us about the project that you’ll be working on this summer! What is it? What do you hope it will accomplish?

Alexis: The Police Data Initiative’s goal is for police departments to use data and technology to build community trust. One facet of this community of practice is having police departments release at least three datasets that have not been released to the public. These types of datasets include: uses of force, police pedestrian and vehicle stops, officer-involved shootings, and more. These data help the communities access key information on police/citizen encounters. I would like to help the Detroit Police Department publicize these datasets and add them to the Detroit Open Data Portal. Additionally, these data should be shared with Code for America and the Police Foundation’s open data portals, aligning with the national movement of transparency and accountability in community policing. By releasing these data, the police department is able to show positive trends in policing techniques, while also being transparent about areas of improvement. Citizens will be equipped with up-to-date and accurate evidence to hold their department accountable for any discrepancies in department practices.

Ayana: I’m excited to create a user-friendly map that illustrates rental housing health and safety across all of Detroit’s neighborhoods. I’ll begin by mapping registered and unregistered rental properties and their health & safety compliance status. From there, I’ll analyze whether there’s a statistically significant correlation between non-compliant housing stock and Early Childhood blood lead levels. If I can determine how to effectively include the data, I may also incorporate “Rent as a Percentage of Household Income” statistics.

I hope that the project will help to illuminate some elements of Detroit residential life that have been unscientifically observed in my neighborhood, and determine whether they’re widely occurring and in which parts of the city. I will focus my work in two key areas: 1) poorly regulated health and safety compliance, often in areas experiencing rising housing costs, and 2) the problem of children being lead-poisoned by unsafe living spaces.

Hopefully, this project will help illustrate where Detroit’s residents are most needed to mobilize for children’s health and safe rental housing.

Sabiha: I am interested in looking at the spatial distribution of substance abuse treatment centers and mental health facilities in locations where there are high concentrations of people involved with the criminal justice system in Detroit—including the flow of people reentering communities from prison and those under parole supervision. Such data could tell us whether there are gaps in access to mental health and substance abuse treatment in neighborhoods with the highest rates of jail-involved populations. Many organizations—such as the Justice Atlas of Sentencing and Corrections—currently maps concentrations of jail-involved populations, but overlaying this with additional information could provide decision makers with useful information about what kinds of services would be most useful in preventing recidivism and alleviating the cyclical nature of recidivism. The end goal of this project is to produce maps that lead to broader questions about resource allocation, such as what is the impact of individuals returning to the same communities they were arrested in?

Tell us something about yourself that would surprise us.

Alexis: I thoroughly enjoy traveling. One of my life goals is to travel to all seven continents. I have been fortunate enough to travel to five out of seven. I still would like to visit Antarctica and Australia.

Ayana: I’m addicted to a cooperative board game imported from Poland, which required translated instructions from the depths of the internet in order to learn to play. It’s addicting, in part, because we almost never win!

Sabiha: This is not particularly surprising, but one of my favorite activities is the process of understanding the layout of a city. I don’t feel like I truly know a city until I can navigate it without a map. But despite my fascination with cities, I have visited relatively few U.S. cities, especially Mid-West and West Coast cities.

What are your favorite types of data?

Alexis: I enjoy looking at statistics and graphs of various education statistics and correctional facility/criminal justice related facts.

Ayana: My favorite types of data are community-driven and collected. I’ve never seen data sets which are better known and more meaningful to ordinary people on the street than those dreamed up and then systematically collected by members of the communities in which they are most impactful.

Sabiha: Prior to coming to D3, I mostly worked with federal-level health insurance data. I prefer working with data that is at the county or city level since my primary interest is in communities and neighborhoods.

What’s your favorite D3 map or data visualization?

Alexis: When I was first introduced to D3 at a presentation about two years ago, I was impressed with the One D Scorecard, a map D3 complied about crime statistics in the city, and a map of formerly incarcerated persons on probation and parole in certain neighborhoods.

Ayana: Working on this project, I can’t stop staring at D3’s map of Detroit’s ‘Percent of Population Under Five’. Of Detroit’s overall population, 7% was under five years of age in 2010. In Southwest Detroit, where I live and play board games with kids, there’s a deep blue cluster that really stands out: signifying that 10% to 15.8% of our population was under the age of five in 2010. In such a sprawling and segregated city, maps like this can help us visualize Detroit’s demographic distinctions on the whole, and more effectively focus certain efforts (like targeting safety improvements for children) in particular.

In terms of design, I‘m pretty taken with the ‘One D Scorecard’. I’ve been thinking through how to balance my desire to illustrate high-dimensional data with the need to maintain ease of visual comprehension, and I think that the designers of the scorecard found an excellent way to take on that challenge.

Sabiha: Motor City Mapping because of the comprehensiveness of the data and the innovative way the data were collected.

Aside from this project, what else do you hope to accomplish during your internship?

Alexis: I hope to gain tangible and transferrable quantitative skills to assist me in statistical work, mapping, grapping, and coding. I would like to become more knowledgeable about GIS mapping and working within Microsoft Access. I am also hoping to learn about the work D3 does with other organizations throughout the city, and how D3 bridges gaps in information for various stakeholders in the city.

Ayana: As someone who didn’t come to this internship with a Social Sciences background, I’m excited to familiarize myself with the available trove of American Community Survey data & better understand what factors we can and cannot (currently!) calculate from.

I’m also looking forward to building an understanding of the data sharing process between municipal and non-governmental organizations, and gaining professional experience to open up future opportunities to do social impact work.

Sabiha: A much more complete and comprehensive understanding of Detroit neighborhoods and the unique challenges facing them!