NYC School of Data 2022

We will kickoff the morning with inspirations from community leaders and City officials.

Over strong community objections, the De Blasio administration passed a comprehensive rezoning in East New York, Brooklyn in April 2016. Neighbors contested the new neighborhood plan, concerned about predatory real estate speculation and rising rental prices. The city responded by forcing developers to build a small percentage of affordable housing. De Blasio called the policy "mandatory inclusionary housing."

This panel aims to assess the impact of the rezoning six years later. First we will briefly summarize some early-stage findings about the state of new construction and affordability in East New York. Then we will focus on how the rezoning has impacted residents of the Nehemiah homes, a large affordable development in East Brooklyn.

We are lucky to be joined by Nehemiah residents Carmen Daniels and Matilda Dyer. The panel will also feature State Assemblymember Latrice Walker, who represents New York's 55th District, which includes Brownsville, East Brooklyn.

Data Performance will be a cutting edge panel on the intersection of data science, performance studies, arts, and critical theory. The session consists of three panelists, and a brief introduction from the curator and moderator. The panelists will define and explore the concept of "data performativity" and how open data could be leveraged by artists and individuals into acts of resistance and change.

Yaakov Bressler (Data Scientist and Theatre Producer) will argue that despite Broadway’s legacy as the center of American theater, historical Broadway data has been mostly unavailable or inaccessible for large-scale analysis. He will discuss why he founded Open Broadway Data to solve this problem, and how such data can be used to enhance the theater experience, improve inclusivity, and shape the future direction of Broadway shows.

Anel Rakhimkhanova (PhD Student at NYU Performance Studies) will draw from a western history of criminology and facial recognition, and look at the works of artist Trevor Paglen and his attempts to present how the biases of modern training data, which are datasets used to teach the software an algorithm, repeat and reestablish the objectives of targeting deviancy. She will introduce the ongoing conversation about how data performs aka participates in the making of our world and how we can reconsider the characteristics centered in it.

Adham Hafez (PhD Candidate at NYU Performance Studies) will discuss how for many years, artists have experimented with the blockchain, and with Web3.0 tools in a visionary manner. However, since early 2021, the rise in popularity of a particular token, called ERC-721 has shaken the art scene. From cartoons to music and performance, non-fungible tokens have allowed artists to sell, auction and share their digital creations with their audiences and fans. The rise in value of these crypto-assets makes us question the future of the art market. Because the blockchain is a publicly accessible ledger, a lot of this data is public as well. He will debate if this could be the beginning for another way of market performance, one rooted in decentrality, accessibility of data, and of provenance records; or, we might quickly see a ‘winner takes it all’ gatekeeper model shaping the future of art and the blockchain.

Why in the world would someone count squirrels? How in the world can you possibly count squirrels without counting the same squirrels twice, or more? And what in the world would you do with all of that data anyway? The Squirrel Census is here to answer all of your "in the world" questions. Plus, the lowdown on their latest project, in which they turned a one-day squirrel count of 24 NYC parks into ... the Squirrel Census Phone Tree.

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Our introduction to open data workshop will introduce you to the fundamental terms and processes needed to understand NYC’s open data. Then, we will move to an interactive game that helps orient you to NYC’s 311 data and how to ask questions from NYC’s open data portal. This workshop will focus on the NYC 311 dataset and a few key municipal tools.

Within analytics, demographic information (e.g., race and gender) is often used carelessly, with a surface level analysis being the end all be all for discussions around issues of disparities and injustice. Such surface level approaches, lacking historical or contextual realities, are insufficient to combat the dark history of demographic data being used to “prove” deficiencies of entire groups. 

During this workshop we will highlight the importance of constructing the “why” behind using demographic data in analyses. In addition, we will discuss the limitations and consequences that are inherent in focusing on such data exclusively.

Finally, using open data on math test results as well as the NYC school directory, we will explore how other factors aside from demographic data explain variation in student math ability

Wondering about open data for schools? The first thing you think about is likely test scores. Test scores are snapshots that many researchers have indicated are biased. This session will seek to engage this community in the world of education open data by addressing one aspect of schools that is often in the public discourse - curriculum. Despite New York City's progressive and long standing open data laws, culture and community, there is no way for a parent, researcher, or concerned citizen to easily look up the curricula used in schools. This problem isn't limited to just curricula (any parents who've tried to find special education services out there?), but we think it's an instructive example. We'll build on your personal experiences to explore why data like curriculum matters in the face of quantifiable test scores, share our approach to liberating curriculum data from PDFs, and situate our efforts in the ecosystem of school of open data in NYC.

Presenters:
Steven Azeka, Program Officer at Robin Hood Foundation Learning + Technology Fund
Tom Liam Lynch, Editor in Chief of InsideSchools and education policy director at The Center for NYC Affairs at The New School
Aankit Patel, Director of STEM Education Programs at City University of New York

This session will discuss the Rebooting NYC report.

In January 2022, the Jacobs Institute’s Urban Tech Hub at Cornell Tech released the final Rebooting NYC report, which proposes new and existing urban tech solutions to some of New York City’s biggest challenges.

After releasing a draft of the report in May of 2021, the Urban Tech Hub consulted with hundreds of tech, civic and community leaders, including current and former city council members and state senators, other elected officials, local business improvement districts and chambers of commerce. The team of 13 researchers, including several Cornell Tech students and alumni, was led by Rohit T. Aggarwala, a Senior Urban Tech Fellow at the Hub.

The final report covers three topics that were not included in the draft: the need for price transparency among ride-hail and other new mobility companies, the opportunity for technology to improve sanitation and recycling, and the potential for in-building battery storage to facilitate a transition to a clean electric supply.

The Stewardship Mapping and Assessment Project (STEW-MAP) surveys civic environmental stewardship groups to provide digital maps and organizational network diagrams that show where, with whom, and how groups are taking care of the local environment in NYC. This presentation gives an overview of STEW-MAP and introduces an emerging real-time tool, called STEW-MAP Live, that will enable our team to better map stewards in real-time. In this presentation, the audience is invited to add groups working in NYC that they know of to this live map. By joining this presentation, you will learn about environmental stewardship, existing open data about stewardship, and ways to consider collecting and updating data on civic organizations.

Civic stewardship groups are not only environmentally focused, they include community development organizations, youth groups, public health groups, and more; all of them play a role in conservation, management, monitoring, education, advocacy, and transformation of NYC’s land, air, and water. STEW-MAP was designed to identify active agents of change working in all communities, to acknowledge the work of informal and grassroots groups, and to extend potential partnerships “beyond the known knowns”. It can also be used to identify “stewardship gaps” -- areas that are underserved by active environmental stewardship and engagement. STEW-MAP utilizes methodologies to identify new and existing organizations working across a landscape and depicts strategic networks, stewardship gaps, and overlaps in activity.

We will host a training session where the audience tries to create a data viz or data story from the following data kits:
1.  NYC Squirrel census
2.  NYC hot spot
3.  LinkNYC hub locations
4.  Popular Baby Names in NYC

Our target audience is High School Students and educators. Our data kits are a self-contained activity set that allows students to create data stories. It contains a data set with guiding questions that help the students derive insights and put together stories.

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Every dataset has a backstory. What ultimately comes to "count" in a dataset often depends on a series of judgments and assumptions held by data creators, the configuration of infrastructures for sorting observations, and political struggles over what should be included or excluded. To interpret the values recorded in datasets responsibly, it is important to understand the social and political contexts that gave rise to their production. This workshop will provide a framework for narrating dataset backstories - studying 'what counts' by analyzing the historical underpinnings of open datasets.

The session will open by way of an example - with a presentation of a backstory of NYC's 311 dataset. From here, the facilitators will lead an interactive session introducing a methodology for piecing together various components of a dataset backstory. Following this presentation, in breakouts, groups will have an opportunity to apply these techniques to narrate "what counts" in a series of NYC open datasets.

The session will emphasize the importance of rich metadata practices and provide resources to recent literature on best practices for data documentation. It will also provide insights as to how biases emerge in datasets and how they can be accounted for in data practice.

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Talk to the analysts from NYC Health behind the New York City Community Air Survey (NYCCAS): 12 years of neighborhood scale street-level air quality data. There may be no better data available to look at spatial variability of air pollution across NYC. Find out about the data collection, how we analyze it, what it can be used for, what are some pitfalls to avoid when using it, what data products are available and where you can find them. We also want to hear about the air quality data that you are collecting and can offer insights into how to visualize that data, what additional data can be useful in providing a more complete picture and how to think about who your audience is/should be.

Capital Planning Explorer (CPE) is a tool for the public and planners to access some maps and data that they need to understand NYC neighborhoods, better plan for investments, and collaborate with one another. CPE makes three databases available on a single platform, allowing users to explore (1) capital projects in the Ten-Year Capital Plan, (2) City facilities, and (3) housing permits on one map.

The session will provide an overview of the tool, followed by a deep dive on the Capital Projects Database. We’ll walk through how we create the database starting with the Capital Commitment Plan from OMB, to how we integrate spatial data from the major capital agencies. We’ll also discuss use cases for both the dataset and the map. These resources can be used as a starting point to answer questions such as:

• What projects are happening in a neighborhood or council district? 
• What other agencies’ projects might impact another project? 
• What capital investments are being made in growing neighborhoods? 
• Are there geographically specific lump sums that can be tapped into? 
• What are the most expensive projects in the City’s Capital Commitment Plan?

The session will close with a conversation about how the audience can use CPE and their suggestions for future improvements.

The recently-approved proposal to rezone Gowanus was accompanied by the City’s first Racial Equity Report to assess the potential impact of the proposed zoning changes on the neighborhood’s demographic makeup. We used this unique opportunity to critically analyze this first-of-its kind study by examining data from the Decennial Census, American Community Survey, and NYC Open Data. In this session, we will present our counter-analysis of the Gowanus Racial Equity Report and open up the conversation surrounding data manipulation, critiques of the racial equity report, and recommendations for future reports.

Our analysis reveals that the boundaries within which data are analyzed significantly impact the demographic and economic profile produced. Interviews with Gowanus residents indicated contestations over the definition of the neighborhood’s boundaries. In its analysis of the demographic composition of Gowanus, we find the Racial Equity Report inflates white residents’ predominance and erases residents of color. In addition, the Report’s characterization of Gowanus as a wealthy neighborhood erases the substantial proportion of the population who may not be able to afford increasing rent as the area becomes more densely developed or who may not qualify for the affordable housing built.

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Our session will describe Emerson Collective (EC)'s process as to how we arrived at the product concept for the “Data Repo”, outline several use cases this platform allows for, and provide a demo of the tool with an NYC-relevant example.

This session will appeal to open data administrators, product managers, and developers who are interested in not just making data open and available, but usable for users downstream.

The Data Repo is more than a code repository or data portal—it is an environment where users can facilitate their entire research and data lifecycle. The Data Repo provides an environment to:

• Work directly with up-to-date data from the cloud
• Share notebooks to (1) collaborate with other researchers within your organization, or (2) disseminate findings to other researchers outside your organization
• Generate visualizations and operationalize insights for other users within their organization (ex. a comms team)
• Post content to share out with the wider research community
• Upskill and learn common coding practices for data retrieval, processing, and publishing

Good data documentation is crucial for understanding what a dataset represents and what it can be used for. Each one of the 3,000+ datasets currently found on NYC Open Data is required to have an accompanying data dictionary that translates the complexity of a particular City operation for members of the public. 
NYC's Open Data Team has been working to improve and standardize data documentation of NYC Open Data datasets, and would love to hear your thoughts! As part of this workshop, you’ll have an opportunity to explore our proposed new data dictionary template, apply it in practice, and share your thoughts on how it can be further improved.

This session features reusable recipes for "regular" folks to quickly validate, join, slice, geocode, enrich, partition & analyze NYC open data, even very large ones like 311, without any specialized tools/training beyond datHere's open-source, data-wrangling command-line toolkit - qsv.

Analyze millions of rows in multi-gigabyte CSV files and turn it into actionable info in a few seconds with simple commands from the command line.

For data analysts, you will also find a practical data-wrangling CLI toolkit that will help you quickly tame your raw data with a simple tool you can quickly integrate into your data pipelines - to enrich, normalize, geocode and even compile and validate against data dictionaries automatically.

General office hour session:

Session will begin with a short overview of the Department of City Planning’s (DCP) open data products and applications available to the public. This will be followed by Q&A from the public on DCP open data. Will reserve time to take questions from participants in the room but highly encourage questions to be submitted ahead of the session via DCPopendata@planning.nyc.gov.

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The Urban Design Division at NYC Planning is responsible for maintaining the NYC 3D Model, which we publish through NYC Open Data. The Model aggregates dozens of publicly available datasets describing the physical city into a single convenient source and is meant to support a wide range of design, visualization and analysis tasks. Recently we have been working to extend compatibility to more 3D modeling tools and enable the use of metadata and attributes alongside geometry.

Using site models and assets provided by the Urban Design Division with the free 3D modeling software Blender, this workshop will equip participants with tools and techniques to model, annotate and render real-world locations in NYC.

This session will engage design professionals (architects, landscape architects, urban designers) including those working in city government, design students, civic technologists, game developers, journalists and members of the general public interested in digital art and urban design.

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OpenStreetMap (OSM) is a collaborative project to create a free editable geographic database of the world. Over the years, OSM has grown to be the go to geo wiki for geospatial information. From the Department of Transportation to CitiBike to Community Boards, OSM is a critical component of New York City’s public realm. 

This session will dive into OSM’s history and how community groups are using OSM to further their advocacy. We will end with how New Yorkers can harness the OSM’s power to map the public realm and develop a new level of data literacy.

The Department of Transportation (DOT)’s Open Streets program is a form of tactical urbanism where previously car-dedicated streets are repurposed into pedestrian only spaces. One way to address any inequities in the program is resourcing existing open streets, with funding, programmatic support, full-time staffers like community organizers, infrastructure, and more. Using NYC’s vast array of open data, specifically about open streets, NYCHA, LinkNYC, traffic, and vision zero, we created a priority metric to identify which of DOT’s existing open streets are among the most deserving for funding/resourcing (similar to “priority A” designations).

Our session will show participants how to create a similar street hierarchy: we created this metric using open data on ArcGIS, but can be easily replicated on QGIS and other free software. This GIS priority metric serves as a model that can be adapted to incorporate different types of data. We want to emphasize that the open street priority metric is designed to be adaptable and reflexive according to changing social, environmental, and political conditions. As strong proponents of participatory research and critical data, we’d love to help participants understand some of the difficulties we encountered and how to troubleshoot them. We’d also present the research we collected, and our results. Specifically, our top three open streets we recommend prioritizing were (1) Murray Hill’s Barton Avenue (due to proximity to vision zero traffic intersections & potential to expand into the LIRR plaza nearby), (2) East Harlem’s East 119th Street (due to proximity to PS 112 and a GreenThumb community garden), and (3) Mott Haven’s Alexander Avenue (due to proximity to four NYCHA complexes).

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Open data really shines when it can be easily, searched, interacted with and combined with other open datasets. Unfortunately, to do this often requires coding knowledge or the use of closed propitiatory platforms. At the Spatial Data Science Center at the University of Chicago, we have been developing a free and open source platform called Matico ( https://www.matico.app/ ) that allows anyone to create rich, interactive open data apps and dashboards with no or very little technical knowledge.

In this session, we will demo how to use Matico to build a sophisticated application that utilizes multiple datasets from the NYC open data portal and encourage people to build their own apps and dashboards to enhance the value of open data.

Our closing keynote will feature community reflections from attendees and a closing presentation from the City's Chief Analytics Officer Martha Norrick.