In September of this year, we launched the MTA’s first Open Data Challenge and called on open data explorers from across the country to use the MTA’s open data on data.ny.gov to build something cool! Participants had one month to create and submit their projects, and to say we were overwhelmed by the response would be an understatement. We received over 100 submissions of incredible quality, with submitters making use of the MTA’s wide range of open data offerings.
As we reviewed these projects, some themes emerged:
- MTA Open Data users are, naturally, big fans of open-source code. A majority of submitted projects were accompanied by a GitHub repository.
- Folks love our ridership data (as do we!). We received so many incredible submissions that made use of our Subway Hourly Ridership data, Bus Hourly Ridership data, and Subway Origin-Destination Ridership estimates.
- Delays, accessibility, ridership trends, and fare policy were all categories that contributors gravitated toward.
- There was so much gratitude for hosting the challenge! Many submissions were accompanied by a sweet note expressing thanks to the MTA for hosting this challenge because the contributors had fun building their project. While thank-you notes did not impact our selection of finalists, our reviewers very much appreciated reading them.
In this blog post we announce the winner of the MTA 2024 Open Data Challenge and highlight some of our favorite finalists. We are so grateful to every single individual who took the time to submit a project and hope that you enjoy reading about a small handful of our favorites!
The finalists
Most interesting research question:
Are NYC Subway Stops Ready for Every Student?
- Contributors
- Taseen Islam
- Olivia Fratangelo
- Huda Ayaz
- Open dataset used
This group of current CUNY students teamed up as part of the CUNY Macaulay Honors College datathon to investigate subway accessibility—a topic New Yorkers are passionate about. But this team went a step further by asking: are subway stations near specialized high schools accessible for students with disabilities? In addition to using MTA’s subway elevator and escalator availability dataset, they layered the NYC Department of Education’s disability demographics dataset to round out the analysis. Plus, their code is open!
Check out this team’s presentation of the data—it clearly lays out their methods and findings, making the report easy to understand and informative for all skill levels.
Most comprehensive view of the data:
The Museum of Transversal Art
- Contributor
- Bianca Ng
- Open datasets used
We received many great submissions that explored the MTA’s Arts Catalog, and Ng’s project stood out to us for her breadth of data insights and the creative use of Tableau. Ng makes smart use of the dashboard, using various data visualization techniques including maps, charts, and infographics.
We loved how Ng took her analysis a step further and thoughtfully visualized the materials used and mediums surrounding the artwork. It really makes you feel like you’re walking through a museum exhibit, as her project title suggests!
Most visually appealing:
Lately on the MTA
- Contributor
- Noah Gunther
- Open datasets used
Gunther’s fun and informative website displays the most recent data on subway, bus, and Roosevelt Island Tram ridership. The project is open-source and makes use of the open data portal’s API to keep the data fresh.
We received a lot of amazing dashboards and web apps that utilized our ridership datasets in creative ways, but this one stood out to us because of its impressive front-end design. The animated trains and buses are so fun, and the data visualizations are simple yet effective at telling a story of where transit rides are taking place.
Most imaginative use of data:
If You Give a Rat a MetroCard
- Contributor
- Will Meyers
- Open dataset used
Meyers’ adorable zine follows the journey of a rat with a MetroCard and how they are likely to travel based on trends in our modeled Subway Origin-Destination Ridership data. As Meyers highlights, rain or shine, New Yorkers make their way to the office on the weekdays. But on weekend evenings, bad weather may be a reason to stay home instead!
While the analysis draws on one of our largest datasets and the supporting code is open-source, we love that the final product makes open data accessible to data enthusiasts of all skill levels.
Most creative storytelling:
Subway Stories
- Contributors
- Jediah Katz
- Marc Zitelli
- Julia Han
- Open dataset used
Subway Stories is a series of vignettes that analyze open data to understand how New Yorkers work, enjoy themselves, and stay connected. The interactive visualization allows users to explore how different groups in NYC travel and effectively uses a complex dataset to glean insight into how folks move about the city. The code for the project is open-source, and the project even picked up some press through Untapped New York.
The Subway Stories project was a favorite of the New York Transit Museum, as it fits nicely with the current exhibit “The Subway Is...” We’re excited to host the contributors at an event on January 23 to learn more about how they built this incredible project! Learn more and register.
The winner
Art off the Rails
- Contributor
- Open datasets used
Dang’s interactive subway map makes the locations of the MTA’s permanent art collection easily accessible. Users can explore the art work at each subway station by clicking the corresponding circle on the map. Her project uses the Svelte JavaScript framework and is open-source.
We love the simple preview cards of each artwork and appreciate that the site seamlessly links back to the MTA’s official website, mta.info, where users can learn more about the piece. The design is dynamic, clean, and polished. The ideas for further improvements to the site are great, and the project documentation in the readme file is excellent.
What pushed this project to the top is that MTA Arts & Design has been looking to build something similar in order to help customers more easily explore the permanent art collection by station location. While we love open data simply for the fun of data exploration, it is incredible when a member of the public can build something that our agency has been dreaming of but hasn’t has the capacity or resources to do ourselves. That’s the true power of open data at work!
According to Stephanie, “working on Art Off the Rails was such a fun and rewarding challenge. Before starting on this project, I hadn't realized how many iconic parts of my commute were actually pieces of art. Diving into the MTA’s permanent art catalog made me realize how much creativity surrounds us even in the most routine parts of our day. It’s been so lovely to explore the different works of art that keep us company as we navigate our intricate little lives. I hope this project inspires others to take a closer look and appreciate the incredible artwork in our subways, especially in those moments when you just missed the train and—dang it, now you have to text your friend that you're running late!”
Explore more with open data
There were truly too many amazing projects to feature in one blog post! If you’re hungry for more, some bonus submissions we loved and highly recommend checking out are MTA Naughty or Nice by Zack Abu-Akeel, Kristina Cheng, Hank Shen, Pauline Wee; Exposure to Art: a MTA Case Study by Jeffrey Starr; and Boroughs Illuminated: A Timeline of Art by Sai Ram Ved Vijapurapu.
While this concludes the 2024 Open Data Challenge, our open datasets are available all year round! You can find MTA data on data.ny.gov 24/7. Make something cool? We’d love to see it! Send us your projects at opendata@mtahq.org.
About the authors
Lisa Mae Fiedler manages MTA’s Open Data Program and had the best time reviewing every single Open Data Challenge submission!
Hannah Spierer is a Senior Manager with MTA’s Policy and External Relations team.