NYC School of Data 2025

The NYC Independent Budget Office (IBO) aims to enhance understanding of New York City’s budget, public policy, and economy through independent analysis. We leverage Open Data in numerous ways to achieve this goal. IBO researchers will present 3 separate projects that used Open Data:

- Brian Cain (Assistant Director) modeled the cost and burden of potential stormwater fees in NYC using geographic data;
- Valerie Gudino (Budget and Policy Analyst) researched IBO police overtime trends, specifically the relationship between NYPD tenure and hours of OT usage of uniform NYPD personnel in fiscal year 2024 using tabular data; finally,
- Emma Gossett (Budget and Policy Analyst) compiled NYC Education Indicators using Department of Education student-level data that is now available Open Data.

This event is perfect for anyone interested in data-driven policy analysis, or the specific areas of environmental, public safety, or education policy. IBO will present all three projects then take audience questions.

What can we learn about NYC's flood risk and flood insurance claims from FEMA’s National Flood Insurance Program (NFIP) data? How can combining NFIP claims data with datasets like 311 street flooding complaints uncover new insights?

Join Mark Bauer and Tiffany Cousins, two civic-minded data enthusiasts, to explore key trends and relationships in FEMA’s NFIP redacted claims data for NYC, investigating how these trends align with broader flood risk and urban dynamics. We aim to answer the following questions:
- How can we analyze trends in the number and amount of NFIP claims over time?
- What are the most costly flood events, and how do they impact flood risk management?
- How can we map the geographic distribution of claims, while being mindful of the limitations with redacted data?
- What can we learn by integrating NFIP claims data with NYC’s 311 street flooding complaints to identify areas of vulnerability?

The ultimate goal is to equip participants with the skills to use Python, SQL, and DuckDB for analyzing NFIP data, while also providing a deep understanding of NYC's flood risk.

The primary takeaway is how insights from FEMA’s NFIP claims data can drive urban policy decisions, improve flood risk management, and help stakeholders make data-driven choices.

Who should attend? This session is designed for individuals with beginner-level proficiency in data analysis, as well as those interested in flood insurance and urban flood risk. Prior experience with the following will be helpful but is not required:
- Interest in FEMA NFIP data and the OpenFEMA API
- Learning about urban flood risk and data-driven risk analysis
- Basic Python or SQL programming and working with geospatial data

The GitHub repo and presentation website will be launched the day before the event.

Crosswalk Labs tracks greenhouse gas emissions over time with unprecedented resolution — scouring hundreds of data sources, running constrained optimization protocols on billions of data points, and bench-marking the results against atmospheric measurements. With support from the Data Foundation, Crosswalk Labs launched an open data portal at open.crosswalk.io, providing free access to neighborhood-level emissions data from 2010-2023.

Director of Solutions Architecture, Danny Sheehan, will present with a member of the Crosswalk Labs climate science team. Individuals and organizations interested in greenhouse gas emissions, energy, and climate science should attend.

We'll present some information on how we source, model and share emissions data, how anyone can access Crosswalk Labs data, and how they can use Crosswalk Labs Open Inventory data. Additionally, since there is some modeled emissions data for some sectors, Crosswalk Labs uses national open data as well as local NYC open data such as NYC Building Energy and Water Data Disclosure for Local Law 84 from NYC Open Data. We will also present how Crosswalk Labs modeled energy and emissions data compare and benchmark against this useful open data provided by NYC.

According to recent articles, NYC ranks amongst the lowest of major cities in voter turnout. In response to this, voting analytics team members from the Harris presidential campaign wanted to explore how to translate ideas for boosting turnout into questions that could be answered using open data – and empower you to do the same.

You can expect a presentation starting with a brief walk through of the types of voting questions the team answered on the campaign using data, a highlight of factors contributing to low voter turnout in recent NYC elections, an overview of how these factors can be translated into questions that can be explored through open datasets, and a dive into a specific case study as an example. The session will close with a facilitated discussion on voter engagement and data to bring folks across the sector together to brainstorm, ideate and learn from one another.