RESEARCH QUESTIONS

This analysis investigates the distribution and characteristics of cultural facilities in New York City, focusing on how these spaces function within the urban landscape. Specifically, the research addresses the following question: How are cultural facilities, such as libraries, museums, and community centers, distributed across the city’s neighborhoods and boroughs, and what are the key attributes that define these spaces in relation to urban social and political dynamics? By examining the geographical spread of cultural facilities and understanding their role in fostering community engagement and activism, this research seeks to uncover patterns of equity, access, and the forces—such as economic and neoliberal urban policies—that shape the physical and social landscapes of New York City.

CONTEXT

New York City is known for its rich cultural landscape, with numerous libraries, museums, and cultural programs scattered across its five boroughs. These facilities serve as community hubs, providing access to arts, education, and social resources. However, the distribution and accessibility of these cultural facilities are influenced by various urban factors, including gentrification, economic inequality, and policy decisions. Understanding how these spaces are distributed, and the characteristics that define them in different neighborhoods, can provide valuable insights into issues of equity, urban development, and social justice. This research examines the geographic distribution of these facilities, the forces that shape their development, and their role in fostering community engagement and activism.

DATA SOURCES AND METHODS

The data for this analysis were obtained from three primary sources:

  1. Facilities Database from NYC Open Data: This dataset provides information on various public and private cultural institutions across New York City, including their names, addresses, and types.
  2. Neighborhood Tabulation Areas (NTA) shapefile from the NYC Department of Information Technology & Telecommunications: This shapefile provides the geographic boundaries of neighborhoods in New York City, allowing for spatial analysis and neighborhood-level comparisons.
  3. In addition, I created a custom 3D Cartesian plot to categorize cultural facilities based on three axes: private vs. public, appropriated vs. dominated, and reactive vs. proactive. I created the data by assigning each facility with a value between -1 and 1, according to all 3 dichotomies.

DATA PROCESSING

CULTURAL INSTITUTIONS WORD CLOUD

RESULTS

This word cloud is a visualization of the types of all NYC-owned or leased property. When hovered over, it shows the number of locations of that sort of site throughout NYC. But does not necessarily reflect the surface area, or amount of space dedicated to that sort of land-use type.

PUBLIC CULTURAL FACILITIES MAP

Click here to view the interactive map

RESULTS

When navigated within, this visualization provides insight into the distribution of cultural facilities across neighborhoods and boroughs. There is a clear concentration in Manhattan and Downtown Brooklyn.

CARTESIAN 3D Map

Click here to view the interactive 3D Cartesian plot

RESULTS

This visualization groups all 70 NYC-owned facility types according to their position on private vs. public, appropriated vs. dominated, and reactive vs. proactive space. It shows clear groupings within the 8 different quadrants where similarities are shared among the neighboring facility types. It shows that there are a significant number of facilities that fall within the appropriated, public, and proactive quadrant,

NEXT STEPS

There is SO MUCH more I wish I could have done with this analysis. I tried and failed to create a summary table of the Cartesian 3D plot. I also struggled to successfully analyze the availability of public park space, within each neighborhood. And investigate the policing of that space. I also would’ve also liked to incorporate additional data sets, such as income levels and demographic information, to analyze how the distribution of cultural facilities intersects with patterns of socioeconomic inequality. Or, conduct a more in-depth case study of neighborhoods with significant disparities in cultural facilities to understand the social, economic, and political factors influencing access to cultural resources.

METHODS

  1. Data Processing: I began by cleaning and preprocessing the raw data from the NYC Facilities Database and the NTA shapefile. This involved removing invalid data points, joining facility data with neighborhood shapefiles, and transforming the coordinates into a common spatial reference system.

  2. Geospatial Analysis: I used spatial joins to match cultural facilities with the neighborhoods they are located in. This allowed for an analysis of cultural facility distribution across different boroughs and neighborhoods.

  3. Data Visualization: I used the leaflet package to create an interactive map, wordcloud2 to generate the word cloud, and plotly for the 3D Cartesian plot. Each visualization was customized to enhance the readability and interactivity, allowing for deeper insights into the data.

  4. Interpretation: I interpreted the results by examining the spatial relationships between facilities and neighborhood characteristics, as well as categorizing facilities based on their public or private nature, and proactive or reactive roles within the urban landscape.