Youth-Driven Map-Making with Open Data / Maps at MIXI Club
NYC Open Data Week – March 24, 2026
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Speakers: Nicole Dubin - Adelphi University; Suraj Uttamchandani - Adelphi University; Matthew X. Curinga - Associate Professor, Adelphi University; Tracy Hogan - Adelphi University; Zachary Kiselev - Midwood High School; Sasha Borysova - Rachel Carson High School; Wen Chen; Gabrielle Dechirico
Moderator: Nicole Dubin - Adelphi University
Introduction to the Maps @ MIXI Club
Nicole Dubin opened the session by introducing the Maps @ MIXI Club and explaining that the event would feature presentations by high school students who had developed research projects using open data and interactive mapping techniques.
Suraj Uttamchandani explained that the project was supported through the Mozilla Foundation’s Responsible Computing Challenge in partnership with organizations including Omidyar Network, Schmidt Futures, Craig Newmark Philanthropies, and the Mellon Foundation.
Matthew X. Curinga described the origins of the club as a continuation of work integrating politics, spatial justice, and responsible computing into undergraduate computer science education. The club was created as an informal collaborative learning environment focused on:
Critical cartography
Critical geography
Spatial justice
Responsible computing
He explained that participants met weekly throughout the fall, hosting guest speakers, conducting GIS software demonstrations, reading articles together, and developing their own projects. The club included graduate students, college students, community members, and high school students from schools including Midwood High School and Rachel Carson High School.
Nicole Dubin explained that students worked collaboratively both in person and remotely through Discord, Zoom, and email exchanges. Students developed research questions, identified appropriate datasets, filtered large datasets for usable information, and wrote code to create interactive spatial visualizations.
Zachary Kiselev – Unequal Pool Distribution and Public Health
Zachary Kiselev, a junior at Midwood High School, presented a project examining unequal public pool distribution across New York City and its possible relationship to public health outcomes.
Kiselev explained that his lifelong experience as a swimmer inspired him to combine athletics and research into a project focused on recreational infrastructure. His central research questions were:
Which NYC neighborhoods have less access to public pools?
How might pool access relate to overall community health?
He argued that athletic infrastructure such as pools, fields, and courts can contribute to healthier lifestyles, and suggested that pool availability could function as a proxy indicator for broader athletic infrastructure investment.
Drawing on existing research, he cited findings that:
Proximity and affordability of sports facilities strongly predict physical activity
Uneven spatial distribution of facilities creates disparities in exercise opportunities
Socioeconomic constraints remain barriers to sports participation
Kiselev suggested future research might examine relationships between wealth, athletic infrastructure, and health outcomes.
To conduct the project, he used NYC Open Data pool inspection datasets and manually cleaned and deduplicated records, reducing an initial dataset of roughly 5,000 entries to just over 1,000 public pools citywide. He spatially joined pool coordinates with New York City community district shapefiles to calculate the number of pools in each district.
He then created maps visualizing pool distribution. Because some districts contained dramatically more pools than others, he manually adjusted map coloring so districts with exceptionally high counts stood out clearly.
Kiselev attempted to correlate pool access with obesity rates as a public-health indicator. However, the statistical relationship proved weak, with very low correlation values. He acknowledged that obesity is influenced by many variables beyond athletic infrastructure, including food access and socioeconomic conditions.
Rather than abandoning the project, he outlined several future directions:
Exploring other health indicators such as heart disease
Incorporating population-adjusted measures
Expanding the study nationally
Using alternative statistical methods
He reflected that unlike many classroom projects, his research did not confirm his hypothesis, which became an important learning experience in itself.
Sasha Borysova – Housing Affordability Dynamics in NYC
Sasha Borysova, a senior research student at Rachel Carson High School, presented a project examining housing affordability dynamics across New York City census tracts from 2010–2022.
Her research questions focused on:
How income and rent changes affected affordability across census tracts
Where rent increased faster than income
How rent burden evolved spatially across the city
Borysova explained that as a New York City resident, she was personally interested in the growing affordability crisis and wanted to visualize how rapidly rising rents compared to income growth.
She reviewed several broader structural drivers of housing affordability problems, including:
Wage growth lagging behind rent increases
Reduced housing construction following the 2008 financial crisis
Restrictive zoning laws
Investment firms purchasing housing primarily for profit
COVID-19 exacerbating preexisting housing pressures
She argued that these factors contributed to a long-term imbalance between supply and demand.
Using U.S. Census data from 2010 and 2022, Borysova created three interactive maps showing:
Median rent change
Income change
Rent burden change
She explained that although income increased substantially in many neighborhoods, rent increases generally outpaced income growth, resulting in increasing rent burdens across most census tracts.
Her findings included:
Most neighborhoods experienced significant rent increases
Very few areas experienced declining rents
Income growth failed to keep pace with rent growth
Households were spending larger shares of income on housing
Borysova concluded that open data made it possible to explore major urban policy issues through spatial visualization and argued that such work could help policymakers better understand housing inequality and zoning policy impacts.
Wen Chen – Racial Disparities in Police Stops Near Schools
Wen Chen presented research examining racial disparities in self-initiated police stops near New York City public high schools.
He began by discussing broader research on discrimination and adolescent stress, noting that elevated cortisol levels associated with discrimination can contribute to long-term health risks such as hypertension and heart disease.
Drawing on prior studies, Wen noted that:
Black and Latinx individuals account for over 80% of police stops in NYC
White individuals account for only 5–6%
Searches of Black individuals are less likely to uncover contraband than searches of white individuals
He argued that these patterns point toward racial bias rather than crime-rate differences.
His study focused specifically on self-initiated police stops — encounters initiated entirely at officers’ discretion rather than through emergency calls. He noted that prior research found many such stops lacked legal justification.
The research question asked:
How does the proportion of adolescents subjected to self-initiated police stops within 700 feet of NYC public high schools differ between predominantly Black and predominantly white schools?
To answer this question, Wen used:
NYPD stop-question-and-frisk data
NYC school demographic data
Public school location shapefiles
He classified schools using enrollment thresholds, defining “predominantly white” schools at 40% white enrollment because white students represent a relatively small proportion of NYC public school enrollment overall.
Wen created 700-foot buffer zones around schools and spatially joined stop records to those zones. His visualizations revealed strong clustering of stops near predominantly Black schools, especially in Harlem, the Bronx, and parts of Brooklyn.
His findings showed:
183 predominantly Black schools had 297 nearby stops
26 predominantly white schools had only six nearby stops
98% of all classified stops occurred near predominantly Black schools
Predominantly Black schools averaged 1.62 stops each
Predominantly white schools averaged 0.23 stops each
He concluded that racial disparities in policing are reflected not only citywide but specifically in the environments surrounding schools.
Wen suggested future research should:
Examine trends across multiple years
Study impacts of policy changes
Explore relationships between policing and academic outcomes such as attendance, GPA, and graduation rates
Gabrielle Dechirico – Restaurant Inspections and Compliance
Gabrielle Dechirico presented a project examining factors affecting NYC restaurant inspection grades. She explained that the project combined interests in inequality, discrimination, and consumer safety.
Her project asked:
Which factors affect whether a restaurant receives an A grade?
The analysis considered variables including:
Cuisine type
Neighborhood income level
Chain versus independently owned restaurants
Inspection violations
Using NYC Department of Health inspection data from NYC Open Data, Dechirico analyzed over 1,700 restaurant inspections.
She explained that NYC’s grading system assigns fewer points to restaurants with fewer violations, with A grades ranging from 0–13 points. She also discussed the possibility that health standards may unintentionally reflect Western cooking norms more than some traditional cultural cooking practices.
Her regression analysis found statistically significant lower probabilities of receiving A grades for Chinese and Indian restaurants, even when controlling for neighborhood income levels. She also found that restaurants inspected more frequently were less likely to receive A grades, suggesting that once restaurants are flagged, they remain under heightened scrutiny.
Dechirico emphasized that the project was not intended to target particular cuisines, but rather to identify patterns that might reflect broader structural inequalities or unequal access to compliance resources.
She proposed several future research directions:
Studying whether chain restaurants benefit from greater institutional support
Examining whether independent restaurants lack compliance resources
Developing city-supported sanitation training programs for immigrant and independent restaurant owners
She argued that the goal should be helping restaurants succeed safely rather than simply penalizing them.
Audience Discussion and Reflections
Following the presentations, Nicole Dubin and the Adelphi faculty opened the session for discussion and questions.
Jazzy Smith from BetaNYC praised the students’ work and asked what surprised them most during their research process.
Zachary Kiselev reflected that the most surprising experience was having his hypothesis disproven. He explained that many school research projects are designed with expected outcomes in mind, whereas this project required him to grapple with inconclusive findings and rethink future research directions.
Matthew X. Curinga commented that many professional researchers avoid presenting findings that fail to confirm their thesis, praising Kiselev for openly discussing null results.
Sasha Borysova discussed how she initially became concerned that her housing hypothesis might be incorrect when she saw income growth in many neighborhoods. This prompted her to create the rent-burden map, which ultimately clarified that rent burdens still increased because rent growth exceeded income growth.
Wen Chen said he was surprised both by the large number of predominantly Black schools and by the sheer number of schools in New York City overall.
The discussion also touched on:
Favorite swimming pools
School demographic composition
Possibilities for future research involving predominantly Asian schools
Broader participation opportunities in the Maps @ MIXI Club
Closing Discussion on Housing Data and Future Research
Matthew X. Curinga asked Sasha Borysova why some neighborhoods appeared to experience rent decreases, describing such trends as unusual in New York City.
Borysova suggested several possibilities:
Small sample sizes
Data limitations
Crime rates
Housing supply changes
She noted that answering the question definitively would require deeper neighborhood-level analysis.
Curinga added that affordable housing developments or changes in total housing stock might help explain such anomalies and encouraged further research using additional census data.
The session concluded with thanks to presenters and attendees, along with invitations for continued involvement in the Maps @ MIXI Club and future Open Data Week activities.
RESOURCES
Maps @ MIXI Club — Adelphi University club on critical cartography, spatial justice, and open data that hosted the four youth projects
Adelphi University — host institution; faculty sponsors Suraj Uttamchandani, Matthew Curinga, and Tracy Hogan
Mozilla Foundation Responsible Computing Challenge — funder of the Maps @ MIXI Club, in partnership with Omidyar Network, Schmidt Futures, Craig Newmark Philanthropies, and Mellon Foundation
NYC Pool Inspections — open dataset used by Zachary Kiselev to map public pool distribution
DOHMH NYC Restaurant Inspection Results — open dataset used by Gabrielle Dechirico and Mariam Khan to predict restaurant hygiene grades
NYPD Stop, Question and Frisk Data — open dataset used by Wen Chen to analyze self-initiated police stops near schools
US Census Bureau data — source of income and rent figures (2010 and 2022) for Sasha Borysova’s housing affordability maps
NYC Open Data — the city open data portal underpinning all four student projects
Center for Constitutional Rights — cited by Wen Chen on the share of self-initiated stops lacking legal justification
BetaNYC — civic organization that co-produces Open Data Week; Jazzy Smith hosted the session’s Q&A