Initiated through a grant from Thomson Reuters, these large-scale experiments aim to explore new critical modes of data visualization.

 
Project
Access to Taxicabs for Unbanked Households: An Exploratory Analysis in New York City
person role
Author(s): 
Juan Francisco Saldarriaga, David A. King
Publication date: 
Friday, January 27, 2017
Publication name, page number: 
Journal of Public Transportation
Description (optional): 
Taxicabs are critical complements to public transit systems. In New York City, ubiquitous yellow cabs are as iconic as the city’s subway system, and the city recently added green taxicabs to improve taxi service in areas outside of the Central Business Districts and airports. In this paper, we used multiple datasets to explore taxicab fare payments by neighborhood and examine how paid taxicab fares are associated with use of conventional banking services. There are clear spatial dimensions of the propensity of riders to pay cash, and we found that both immigrant status and being “unbanked” are strong predictors of cash transactions. These results have implications for local regulations of the for-hire vehicle industry, particularly in the context of the rapid growth of services that require credit cards to use. At the very least, existing and new providers of transit services must consider access to mainstream financial products as part of their equity analyses.
Intro text (homepage): 
In this paper, we used multiple datasets to explore taxicab fare payments by neighborhood and examine how paid taxicab fares are associated with use of conventional banking services. There are clear spatial dimensions of the propensity of riders to pay cash, and we found that both immigrant status and being “unbanked” are strong predictors of cash transactions. These results have implications for local regulations of the for-hire vehicle industry, particularly in the context of the rapid growth of services that require credit cards to use.
Lead image: 
Author Last Names for table: 
King, Saldarriaga
Publication short title (carousel): 
Access to Taxicabs for Unbanked Households
Is Website?: 
no
dashboard_sort_date: 
Friday, January 27, 2017
(currently rendering default node template)
 
Just Published: Access to Taxicabs for Unbanked Households

"Access to Taxicabs for Unbanked Households: An Exploratory Analysis in New York City," by David King and CSR Research Scholar, Juan Francisco Saldarriaga has been published in the Journal of Public Transportation. In this paper, we used multiple datasets to explore taxicab fare payments by neighborhood and examine how paid taxicab fares are associated with use of conventional banking services

Abstract: Taxicabs are critical complements to public transit systems. In New York City, ubiquitous yellow cabs are as iconic as the city’s subway system, and the city recently added green taxicabs to improve taxi service in areas outside of the Central Business Districts and airports. In this paper, we used multiple datasets to explore taxicab fare payments by neighborhood and examine how paid taxicab fares are associated with use of conventional banking services. There are clear spatial dimensions of the propensity of riders to pay cash, and we found that both immigrant status and being “unbanked” are strong predictors of cash transactions. These results have implications for local regulations of the for-hire vehicle industry, particularly in the context of the rapid growth of services that require credit cards to use. At the very least, existing and new providers of transit services must consider access to mainstream financial products as part of their equity analyses.

Download the full article here

 

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CSR Researcher Juan Francisco Saldarriaga to Speak at Bloomberg – Data for Good Exchange
Sep 15, 2016 — Spatial Information Design Lab

Juan Francisco Saldarriaga will be presenting his recent paper ‘Access to Taxicabs for Unbanked Households’ during the Data for Good Exchange yearly conference at Bloomberg. The conference will take place on September 25th, 2016. Here’s a description of the presentation: Taxicabs are a critical aspect of the public transit system in New York City. Ubiquitous yellow cabs are as iconic as the city’s subway system, and the city recently added green taxicabs to improve taxi service in areas outside of the central business districts and airports. In this paper we use multiple datasets to explore taxicab fare payments by neighborhood and examine how paid taxicab fares are associated with use of conventional banking services. There are clear spatial dimensions of the propensity of riders to pay cash, and we find that both immigrant status and being ‘unbanked’ are strong predictors of cash transactions. These results have implications for local regulations of the for-hire vehicle industry, particularly in the context of the rapid growth of services that require credit cards. At the very least, existing and new providers of transit services must consider access to mainstream financial products as part of their equity analyses.

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Exit
An immersive installation that investigates global human migrations, updated to coincide with Cop21 in December 2015.
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Global populations are unstable and on the move. Unprecedented numbers of migrants are leaving their countries for economic, political and environmental reasons. Exit, immerses the viewer in a dynamic presentation of data documenting contemporary human movement. Statistics documenting population shifts are not always neutral and the multiple efforts to collect them are decentralized and incomplete. Here the data are repurposed to build a narrative about global migration and its causes. The viewer enters a circular room and is surrounded by a panoramic video projection of a globe which rolls around the room printing maps as it spins. The maps are made from data which has been collected from a variety of sources, geocoded, statistically analyzed, re-processed through multiple programming languages and translated visually. The presentation is divided into narratives concerning population shifts, remittances, political refugees, natural disaster and sea-level rise and endangered languages.

Originally completed in 2008, EXIT has been fully updated to coincide with Cop21, the United Nations Conference on Climate Change and reflects data from 2015. On view at the Palais Tokyo in Paris from November 25, 2015 – January 10, 2016.

Population and urban migration. Photo © Luc Boegly

Project Team
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Columbia Data Science Society Lecture - Next Level Data Visualization

Juan Francisco Saldarriaga will be presenting multiple center projects emphasizing process and code for the Data Science Society at Columbia University. He will describe in detail how to gather data from public APIs and how to use different visualization tools to produce compelling graphics.

Read more.

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Project
Port to Port
person role
Author(s): 
Juan Saldarriaga, Laura Kurgan, Dare Brawley, Jen Lowe
Publication date: 
Tuesday, July 8, 2014
Publication name, page number: 
Spatial Information Design Lab
Description (optional): 
Ninety percent of all goods worldwide are moved by ship, but shipping is mostly invisible. More than 300 million Metric Tons of energy are shipped in and out of the United States each year, in 60,000 shipments. This project presents the ports and paths of the 2.7 billion Metric Tons of energy shipped through more than 90 US ports from 2002 - 2012. Using data assembled by Thomson Reuters, Port to Port maps global oil shipping routes as well as other forms of energy navigating ocean territories to and from the United States. Using D3 as an interactive web platform we designed a map interface that is scaled globally while embedded with local stories about energy movement from port to port. Data can be viewed across time, which reveal changes in patterns of movement as the geopolitics, price of oil, and conditions at specific ports change.
Intro text (homepage): 
Ninety percent of all goods worldwide are moved by ship, but shipping is mostly invisible. More than 300 million Metric Tons of energy are shipped in and out of the United States each year, in 60,000 shipments. This project presents the ports and paths of the 2.7 billion Metric Tons of energy shipped through more than 90 US ports from 2002 - 2012. Using data assembled by Thomson Reuters, Port to Port maps global oil shipping routes as well as other forms of energy navigating ocean territories to and from the United States. Using D3 as an interactive web platform we designed a map interface that is scaled globally while embedded with local stories about energy movement from port to port. Data can be viewed across time, which reveal changes in patterns of movement as the geopolitics, price of oil, and conditions at specific ports change.
Lead image: 
Author Last Names for table: 
Project Lead: Juan Francisco Saldarriaga
Publication short title (carousel): 
Port to Port
Is Website?: 
yes
dashboard_sort_date: 
Tuesday, July 8, 2014
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Project
Jumping the Great Firewall
person role
Author(s): 
Dan Taeyoung
Publication date: 
Tuesday, April 8, 2014
Publication name, page number: 
Spatial Information Design Lab
Description (optional): 
This project visualizes a relatively new phenomenon: online free expression in China. It examines some innovative strategies employed by users of Weibo, a Twitter–like micro–blogging platform, in order to avoid government censorship bloggers post images as text. Images are much more difficult for automated search programs to analyze, which allows image-based content to spread more widely before it is detected and removed. Taking advantage of this, some users now turning writing into images, taking screenshots of their own and others' controversial posts before they're removed, then posting and re–posting them. The project visualizes Weibo posts that were posted and deleted between September 8th to November 13th, in 2013.
Intro text (homepage): 
This project visualizes a relatively new phenomenon: online free expression in China. It examines some innovative strategies employed by users of Weibo, a Twitter–like micro–blogging platform, in order to avoid government censorship bloggers post images as text. Images are much more difficult for automated search programs to analyze, which allows image-based content to spread more widely before it is detected and removed. Taking advantage of this, some users now turning writing into images, taking screenshots of their own and others' controversial posts before they're removed, then posting and re–posting them. The project visualizes Weibo posts that were posted and deleted between September 8th to November 13th, in 2013.
Lead image: 
Author C4SR: 
Author Last Names for table: 
Project Lead: Dan Taeyoung
Publication short title (carousel): 
Jumping the Great Firewall
Is Website?: 
yes
dashboard_sort_date: 
Tuesday, April 8, 2014
(currently rendering default node template)
 
The Art of Data Visualization: Activity Mapping Workshop

Juan Francisco Saldarriaga will be leading a workshop on how to download API data using Python in the context of the Art of Data Visualization conference to be held at Columbia University on April 7th. The workshop will take place at the Digital Social Science Center (215 Lehman Library) from 10:30 AM to 11:30 AM.

Here’s a description of the workshop: This workshop will introduce you to basic Python programing and to social media APIs. Students will learn how to write basic Python code to import data, query API's and extract information, and export the results in formats that can be used for analysis or mapping.

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The Art of Data Visualization: Activity Mapping Lecture

Juan Francisco Saldarriaga presented two recent center projects in his talk ‘Activity Mapping’ during the Art of Data Visualization conference held at Columbia University on April 6th. The talk took place at the Davis Auditorium (room 412 Schapiro CEPSR) at 10:50 AM.

Here's a video of the talk:

Here’s a description of the talk: Foursquare check-ins? Citibike rides? Open data can tell us a lot about our cities and how we use them: what we think of them, how we feel about them and how we live in them. In this talk we present two research projects that use this data to explore and understand how people live in New York. We analyze check-in data from Foursquare and Facebook to examine how social media activity relates to socio-economic factors and what this kind of data can tell us about how people feel about the modern city. We also analyze Citibike ride data visualizing the imbalance problems the system faces. All of this, while also exploring multiple ways of representing spatial data.

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The Banking Divide For Taxi Access: Evidence From New York City
In this project we use multiple datasets to explore taxicab fare payments by neighborhood and examine how access to taxicab services is associated with use of conventional banking services.
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Since 2008 yellow taxis have been able to process fare payments with credit cards, and credits cards are a growing share of total fare payments. However, the use of credit cards to pay for taxi fares varies widely across neighborhoods, and there are strong correlations between cash payments for taxi fares, cash payments for transit fares and the presence of unbanked or underbanked populations. In this paper we use multiple datasets to explore taxicab fare payments by neighborhood and examine how access to taxicab services is associated with use of conventional banking services.

Green Cab Origins
Green Cab Origins

Taxicabs are a critical aspect of the public transit system in New York City. The yellow cabs that are ubiquitous in Manhattan are as iconic as the city’s subway system, and in recent years green taxicabs were introduced by the city to improve taxi service in areas outside of the central business districts and airports. Approximately 500,000 taxi trips are taken daily, carrying about 800,000 passengers, and not including other livery firms such as Uber, Lyft or Carmel. Since 2008 yellow taxis have been able to process fare payments with credit cards, and credits cards are a growing share of total fare payments. However, the use of credit cards to pay for taxi fares varies widely across neighborhoods, and there are strong correlations between cash payments for taxi fares, cash payments for transit fares and the presence of unbanked or underbanked populations.

These issues are of concern for policymakers as approximately ten percent of households in the city are unbanked, and in some neighborhoods the share of unbanked households is over 50 percent. In this paper we use multiple datasets to explore taxicab fare payments by neighborhood and examine how access to taxicab services is associated with use of conventional banking services. There is a clear spatial dimension to the propensity of riders to pay cash, and we find that both immigrant status and being ‘unbanked’ are strong predictors of cash transactions for taxicabs. These results have implications for local regulations of the for-hire vehicle industry, particularly in the context of the rapid growth of services that require credit cards. Without some type of cash-based payment option taxi services will isolate certain neighborhoods. At the very least, existing and new providers of transit services must consider access to mainstream financial products as part of their equity analyses.

Overall there are observable differences for cash payments by taxi type, location, trip origin and trip destination. It is impossible to know what characteristics differ between a typical yellow cab passenger and a typical green cab passenger, but something leads green cab passengers to use cash far more often than yellow cab passengers. The results shown on the maps suggest that there is a spatial factor in play.

In all maps there are stark lines that demarcate where riders predominately use cash (shown in yellow) and where they use credit (shown in blue). The areas marked with yellow are the places where cash is king. With the exception of a credit card hotspot surrounding Columbia University in Morningside Heights Manhattan payment types divide cleanly along income lines, where wealthy neighborhoods flanking Central Park (the empty white rectangle in the middle of the map surrounded by blue to the south and yellow to the north) on the Upper West Side and Upper East Side pay for taxi trips mostly with credit cards and poorer neighborhoods to the north in Spanish and Central Harlem are dominated by cash. One interesting aspect is that the socio-demographic characteristics of neighborhoods seemingly play a large role in determining payment type. It is likely that the cash or credit choice is a function of access to a bank account, for which these spatial data are a good proxy. Another takeaway is that much of the city still does not produce a lot of taxi trips and there is not enough data to present primary payment types at all.

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