About Us:

Data Driven Detroit (D3) provides accessible, high-quality information and analysis to drive decision-making that strengthens communities in Southeast Michigan.

Meet the D3 Summer Interns! (Part 2)

In our last post, we introduced D3’s pilot summer internship program and interviewed our three data analysis interns – Alexis Farmer, Ayana Rubio, and Sabiha Zainulbhai.  Now, we’re introducing Jessica Waligora, our Web Development Intern, and Lucas Munson, our Marketing/Outreach Intern.  As with our three data analysis interns, Lucas and Jessica are working on community-focused projects of their own invention, adapting the traditionally internal focus of their positions into design and outreach  initiatives that will have significant benefits for the Detroit community!



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

Jessica:  For many people who have a history in Detroit it is usually because they grew up in Detroit. My journey with Detroit started with my love for art. I came to study Advertising Design at my dream school, College for Creative Studies (CCS), which is located in Midtown. I pursued this internship for the experience it would give me. I also really like what Data Driven Detroit stands for, and want to be a part of it.  I would also like to better understand what I can bring to the organization.

Lucas:  Although I was raised in Boston, I always grew up a Detroit kid. While all of my friends were wearing Red Sox jerseys and celebrating another Patriots Super Bowl victory, I was always proudly wearing my Detroit Tigers hat and Chauncey Billups jersey. My love of Detroit was not solely rooted in sports, either. As a kid I loved maps, and it was not long before I decided to pursue a degree in city planning. I then constantly found myself drawn to the Motor City, and leapt at this opportunity to work here in Detroit. As the communications intern, I find myself constantly placed in positions to meet new people and see the exciting work D3 is doing for the city. Therefore, as someone who did not get the chance to grow up here, I could not have asked for a better opportunity to truly begin to understand the beautiful city of Detroit.


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

Jessica:  I am the web development intern and I will be working on a few different projects this summer. In a broad spectrum, I will be taking the interactive tools that Data Driven Detroit has to offer and converting them into a format that the public can use. I will also be helping with the development and upkeep of Data Driven Detroit’s new website. Even though that was my specific intern project, I was also added to the communications/marketing team given my experience with that in my degree. I hope that it will help get D3’s name out in to the Detroit community and make people more aware of the resources they have access to.


Lucas:  This summer, I am working on a project that aims to make our data more useful and accessible. While all of D3’s data is available online, many people do not regularly have access to a computer, or simply prefer to see things on paper (like myself). My goal is to create maps and other forms of information that are relevant to a particular community, and make them available for any resident by placing them in community centers, libraries, and other common places. I hope this will provide an additional resource for community leaders and organizations to help them continue the incredible work that they do in their respective communities.


Tell us something about yourself that would surprise us.

Jessica:  I played softball for 9 years and while on my JV softball team in high school, I was awarded with the MVP title that year.

Lucas:  I am actually from Brazil, and moved to the States as a kid. That’s why I love soccer!


What are your favorite types of data?

Jessica:  My favorite types of data are demographic and socioeconomic data.  They tell you about people and their stories in a numeric format in numeric format.

Lucas:  Population, for sure.  I love looking at populations of different cities, states, neighborhoods, anything. I especially enjoy looking at population trends over time, for just a few decades of figures can really tell a story.


What’s your favorite D3 map or data visualization?

Jessica:  My favorite D3 map would have to be the Open Data Portal. It takes some of the information D3 has collected over the years and makes it interactive.    The best part is that all of the data offered on the Open Data Portal is free to download, which includes tables, charts, and datasets.

Lucas:  I really enjoy the work D3 did with Motor City Mapping. The incredible detail and diligence required to track every parcel of land in this enormous city is mind-boggling. Plus, there is no better way of understanding Detroit when I am hundreds of miles away than to spend countless hours clicking around and seeing the state of every single neighborhood.


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

Jessica:  I hope to become more involved in Detroit’s community, further my own and others’ personal and career development. In order to work on any of these projects here, each person has to really want a brighter future for Detroit, and the best way to do that is to become more involved with the community. Most, if not all, of the D3 staff members are already heavily involved with the community and I would like to follow in their footsteps. Also, going into anything, especially a new opportunity, you need to understand not only what you can receive but what you can give others. By the time my internship is over, I hope to have grown a lot as a person and in my career and to help others grow as well.

Lucas:  The wealth of knowledge on anything ranging from data analysis to computer programming here at Data Driven Detroit is incredible. It would be foolish of me if I did not use this opportunity to learn from all the brilliant people here at D3 that make this all possible. I hope to become more refined in programs such as ArcGIS and Access. In addition, I hope to learn more about this city, and look forward to seeing and learning about all the incredible work being done in every corner of Detroit.

*          *          *

We thank you for taking the time to get to know our summer interns!  We’re looking forward to a fantastic summer with these fine individuals.  We plan to keep updating this blog with additional content from the program over the course of the summer, so be sure to check in from time-to-time to learn more about their experiences with D3!

Meet the D3 Summer 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.

OLYMPUS DIGITAL CAMERAAyana:  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!

New Data Portal Design


By looking at best practices from other organizations and taking lessons learned from our own implementation, we’ve created a new data portal front page that is more aesthetically pleasing, simpler to navigate and more intuitive.

As one of the very first implementations of the ArcGIS Open Data platform, the D3 data portal beta was good at the time, but not particularly well designed. While the functionality was all there, the initial interface that welcomed people needed a face-lift. We think that you’ll agree that the new interface is an improvement, but in case you aren’t sure why we changed a good thing, here are the highlights about what we’ve done.

First, we’ve stripped out a bunch of text. Our new design offers a less-is-more approach that helps users understand the purpose of the site as well as its contents without requiring users to spend time reading the fine print.  If a lot of text is needed to explain to users how to use a site, it could probably be designed better. In our case, we had limited time initially to design a spiffy interface for our beta product, so we needed to rely on text.

Next, we designed graphics consistent with the D3 brand, so people intuitively know they are working with a D3 product and data. We stand for quality data at D3, and we think that people will feel confident using data if they understand that it is provided by D3.

Finally, we simplified the site, taking away extraneous purposes. Instead, we focused on three major functions:

  1. Locate, distribute and share data: This is the core function of the data portal and it is now more obvious that the data portal is made to locate and access data.
  2. Connect community members that need data with Data Driven Detroit: While we strive to make as much data available through the portal, there will always be a need for staff to help explain how to use data, what else is available and to perform further analysis.
  3. Expose a platform for developers to create new applications that use our data to serve the community:  Our data portal is built on a platform which has a full-featured and well-documented API. The new data portal interface makes it more clear how to access our data through the API.

In the future, we plan to further integrate our data platform architecture into the organization and make more of the data that we produce available to the public. In addition, we are undergoing a major redesign of the D3 web page, which will also work closely with our new data architecture. Look for the new website this summer.

At Data Driven Detroit we strive to make data more accessible for our communities and we feel that this is a big step toward doing that. We would welcome feedback about our new data portal, as well as any ideas for future improvement or new data requests. We hope you like our new data portal experience.

The new data portal interface can be found at the URL: portal.datadrivendetroit.org.

If you’d prefer to use the old interface, it will continue to be available for a limited time at: beta.d3.opendata.arcgis.com.

Email: askD3@datadrivendetroit.org
Facebook: DataDrivenDetroit
Twitter: @D3Detroit

Moms, Place, and Low Birth Weight, Part 3: Place and Race Together

This is the third in a three-part blog series examining correlates of low birth weight in babies born in 2010, 2011, and 2012 in Detroit, Wayne County outside of Detroit, Oakland, and Macomb counties.  Low birth weight (LBW), defined as 2500 grams or less[1], is a significant contributor to Detroit’s alarmingly high infant mortality rate.[2] We offer this analysis in the belief that a better understanding of factors influencing birth weight can help reduce the mortality rate.

The first blog post looked at the associations between a baby’s birth weight and the mother’s age, education, marital status, ethnicity, and race; the level of prenatal care she received; and the area of residence for women within the city of Detroit.  That analysis showed that birth weight was related to the mother’s characteristics for women living in Detroit, although the strength of the relationship depended on the characteristic.

The second blog post compared the findings for Detroit to those for the “Metro Region” ­­–  defined as Wayne County outside of Detroit, Oakland County, and Macomb County — on the same characteristics, in effect asking, “Does place matter?”  We found that by including place of residence along with the mother’s characteristics we gained an even better understanding of demographic influences on birth weight. So yes, place does matter for birth weight for many of the characteristics.

In this third blog post we take the examination of associations between mothers’ demographic characteristics and their children’s birth weight even further by adding another layer to the analysis: the mother’s race.  Because a major difference between Detroit and Metro Region women giving birth during this period is the racial composition of the two groups, and we know that race can have major implications for an individual’s opportunities and well-being, we investigate the effects of combinations of place and race on LBW rates for the various characteristics of the mother.

Source of data

The data for this study came from birth certificate records of babies born in 2010, 2011, and 2012 with the mother’s residence in Wayne, Oakland, or Macomb County. The first blog post in this series described the source in detail.  For the present analysis, we included only those women who were listed on the birth certificate as either Black/African American or White, and created four place-race groups:  Detroit Black, Metro Region Black, Detroit White, and Metro Region White.  In the charts that follow, each group has its own consistent symbol:

(1)  Green diamond:  Detroit Black

(2)  Blue square:  Metro Region Black

(3)  Red triangle:  Detroit White

(4)  Green square:  Metro Region White

On some of the charts it will appear as though only three groups are represented.  This happens when two groups have the same value, resulting in overlapping symbols or when the number of births is so small that the percentages would be unreliable, in which case we’ve removed the symbol.

Mother’s age, race, and place of residence

Figure 1 and Table 1 illustrate that across the age groups, Blacks had higher rates of LBW infants than Whites in both Detroit and the Metro Region, with a slight advantage overall for Blacks residing in the Metro Region rather than in Detroit.

Figure 1 also shows a common pattern among three of the groups – rates that are high for teens, dip down for women in their 20s, and then get worse as mothers get older. Detroit Blacks, Detroit Whites, and Metro Region Blacks had increasing rates of low birth weight babies from ages 20-24 or 25-29 on.[3]  Particularly striking is the percentage of low birth weight babies for Detroit Blacks ages 35 and older (18%).

However, there is a counter trend among Metro Region Whites.  Their rate of low birth weight babies decreased as age increased until age 35 and above.


Table 1: Percentage of LBW singleton births by mother’s age, area of residence, and race, Detroit and Metro Region, 2010-2012

Third LBW blog post Figure 1

Figure 1

Mother’s education, race, and place of residence

In the second blog post we saw that the rate of low birth weight was related to educational attainment in the same way for women living in Detroit and women living in the Metro Region: namely, the greater the educational attainment, the lower the rate of low birth weight.  And that relationship does not change when we add race to the analysis.

The additional information we get by controlling for race is that the LBW rates for Black women are essentially the same or nearly so whether the women live in Detroit or the Metro Region.  Furthermore, the rates of LBW are consistently higher for Blacks than for Whites in both areas[4].  It is also the case that the LBW rates for Detroit Whites are slightly higher than for Metro Region Whites but are closer to Metro Region Whites’ rates than to the LBW rates for Metro Region Black women.


Table 2: Percentage of LBW singleton births by mother’s education, area of residence, and race, Detroit and Metro Region, 2010-2012

Third LBW blog post Figure 2

Figure 2

Mother’s marital status, race, and place of residence

In the first two blog posts, we showed that married women in Detroit and the Metro Region had lower rates of LBW than never married women.  However, Figure 3 and Table 3 illustrate that among married women, the rates of low birth weight were higher for Black women than for White women regardless of area of residence.

Among never married women, Blacks had nearly identical LBW rates whether they lived in Detroit or the Metro Region. On the other hand, never married Detroit White women had a somewhat higher rate than Metro Region White women, placing them midway between Black women and Metro Region White women, a pattern we saw above with age and education.


Table 3: Percentage of LBW singleton births by mother’s marital status, area of residece, and race, Detroit and Metro Region, 2010-2012

Third LBW blog post Figure 3

Figure 3

Mother’s adequacy of prenatal care, race, and place of residence

The relationship between adequacy of prenatal care and birth weight follows the same pattern we have seen with age, education, and marital status:  Black LBW rates are higher than White rates across all three levels of prenatal care adequacy; Black rates in the two regions are more similar to each other than to Whites’ rates; and Detroit Whites’ LBW rates lie midway between the Metro Region’s White rates and Black rates.  Note that the gap between Blacks and Whites’ rates is greatest for adequate care (Figure 4 and Table 4).  Also observe that an intermediate level of prenatal care raises the likelihood of a low birth weight baby relative to an adequate level of care more for Whites than for Blacks.  It is an inadequate level of care, however, that is particularly detrimental to Blacks.


Table 4: Percentage of LBW singleton births by adequacy of prenatal care, area of residence, and race, Detroit and Metro Region, 2010-2012

Third LBW blog post Figure 4

Figure 4

Summary and Future Directions

We began this study of influences on babies’ birth weight with the knowledge that low birth weight is closely related to an increased risk of infant mortality, an especially pressing problem in Detroit.  We wanted to know whether there are some relatively easily identified demographic characteristics of the mother that are associated with the likelihood of having a low birth weight baby.  The Michigan birth certificate contains a number of such characteristics.  We selected seven for our investigation: the mother’s age, education, marital status, ethnicity, and race; the level of prenatal care she received; and her area of residence (Detroit or the Metro Region).

This third blog post builds on the first two and adds a third layer of analysis.  It is clear that a major difference between Detroit and the Metro Region is the racial composition of the populations.  It is equally clear that one’s race can have profound implications for one’s well-being and opportunity.  So the question became, “Would knowing a woman’s race increase our knowledge of the likelihood of her having a low birth weight baby beyond what we know from her other demographic characteristics and her area of residence?  (For reasons of sample size, we restricted this analysis to women classified on the birth certificate as either Black or White.)

For the analysis we constructed four place-race groups:  Detroit Blacks; Detroit Whites; Metro Region Blacks; and Metro Region Whites.  Whether we examined the relationships by women’s age, education, marital status, or level of prenatal care, the results were the same:  Blacks consistently had higher rates of low birth weight for their babies than Whites, whether they lived in Detroit or the Metro Region.  Detroit Whites occupied an intermediate position, generally having somewhat higher rates than Metro Region Whites but typically lower rates than Black women in either region.  In short, both place and race were significant factors for a baby’s birth weight.

However, it appeared that race was more influential than place for the LBW rate among Black women.  This was particularly the case when we looked at the rate by educational attainment and level of prenatal care.  For these two variables, Black women’s rates were very similar whether the women lived in Detroit or the Metro Region.  Place seemed to play a more influential role for White women than for Black women, since Metro Region Whites generally had lower LBW rates than Detroit Whites.

A word of caution:  The results reviewed in these three blog posts were intended only to stimulate conversation about demographic factors influencing birth weight, not to identify which of the factors were most important.  In this initial investigation, we chose to examine the influence of selected demographic characteristics one at a time.   The included characteristics are ones that are recorded on the birth certificate, but there are many other factors such as household income that we have not included in our analyses.  Some of these were not included because the data do not exist on the birth certificate or if they are on the birth certificate, are unreliable.  Other measures such as the mother’s health were excluded as being outside our area of interest.

Looking ahead, there are many other analyses to conduct that will give us a more nuanced understanding of variations in birth weight.  A more insightful analysis, for example, will examine the simultaneous influence of several variables on birth weight.  We may know that educational attainment is related to birth weight in a certain way and even know how the relationship is moderated by race and place of residence.  But if we really want to be able to identify women most likely to have LBW babies, we will want to know which factors are most predictive, and that means we will need to consider multiple factors simultaneously.  This will be the thrust of a future investigation.


[1] Very low birth weight is defined as less than 1500 grams.  In this analysis, very low and low are aggregated as “low” birth weight.

[2]  Brown, Sally.  “Detroit Task Force to Reduce Infant Mortality,” Henry Ford Health System News and Research, October 19, 2011.

[3] Because the total number of Detroit Whites is small, (2,511) the LBW percentages for Detroit Whites broken down by age should be viewed with caution.

[4] Because of the small numbers of Metro Region Blacks with an eighth grade education or less and of Detroit Whites with an Associate’s degree, we have eliminated them from Figure 2 and Table 2.

Getting “Trashed” on Opening Day, 2015

We at D3, like many people throughout Detroit, love the Tigers Opening Day celebration. It is a special day that marks the beginning of warm weather, outdoor activities and of course another hopeful season of baseball. Each year throngs of Tigers fans (and those who like an excuse to celebrate) from all over the region head downtown to eat, drink and be merry in advance of the first Tigers home game. Today, as in previous years, thousands of cabin-fever-afflicted fans will visit their favorite tailgating spots, have a few beverages, grill a few ‘dogs, cheer on our team…. and then leave behind a ton of trash. Unfortunately, while the celebration is great for Detroit, it has typically left behind a mess that can take days to clean up.

Tasked with cleaning up much of this trash is Clean Downtown, a program paid for by downtown businesses that picks up trash from about 200 receptacles placed strategically throughout the central business district. They also pick it up from sidewalks, the middle of the street, and everywhere else. According to the Ryan Epstein, who manages the Clean Downtown program for the Downtown Detroit Partnership (DDP) in conjunction with Goodwill Industries, Detroit’s Opening Day celebration produces around ten tons of garbage, which is one of the their biggest trash days of the year. To put that in perspective, a Ford Focus weighs about one and a half tons.

While it is easy to pick up trash contained in cans, much of the Opening Day trash inevitably ends up on the ground, creating more of a burden for the Clean Downtown program and the hard-working crews who help to pick up Detroit’s streets and sidewalks. To help the Clean Downtown crews this opening day, we’ve created a map showing the locations of the receptacles.


If you’re a data geek as well as a baseball fan, we’ve made the receptacle locations downloadable via our data portal. The data include the locations of the Clean Downtown receptacles as well as those public receptacles supplied by the city.

Enjoy opening day, and thanks for helping to keep downtown beautiful.

Moms, Place, and Low Birth Weight, Part 2: Does Place Matter?

This is the second in a three-part series examining correlates of low birth weight in babies born in 2010, 2011, and 2012 in Detroit, Wayne County outside of Detroit, Oakland County, and Macomb County. Low birth weight (LBW), defined as 2500 grams or less[1], is a significant contributor to Detroit’s alarmingly high infant mortality rate.[2] [Read on...]

Data Show Where Detroit’s Students Live

Detroit is a big place, and the demand for schools can’t be the same equally across the city, especially since there are such large differences between thriving and disinvested areas. Because the education landscape continues to be a topic of much discussion, we recently put an approximated student location data set to good use by [Read on...]

Exploring Student Dispersion Maps

Since the 2011-12 school year, Data Driven Detroit (D3) has created a series of maps that illustrate the spatial patterns related to where students from different areas in Detroit attend school or where students from different schools live (see our previous blog post introducing the project). This year’s data, from the October 2013 student count, [Read on...]

Moms, Place, and Low Birth Weight, Part 1: Detroit

In an influential January 30, 2014 Detroit News article entitled “Detroit is Deadliest City for Children,” the author, Karen Bouffard, wrote, “In 2010, Detroit (population about 713,000) and Cleveland (population about 390,000) had the highest infant mortality rates of Big City America: 13.5 deaths for every 1,000 live births — higher than [Read on...]

Uphill Both Ways: Where are the Jobs in Metro Detroit?

This post is the second in a series focused on employment and commuting patterns in Detroit and the surrounding region.

In the first post of the “Uphill Both Ways” series, we looked at employment of lower-earning residents in Detroit, Hamtramck and Highland Park in communities that have opted out of the SMART public transportation [Read on...]