CitiBike Rebalancing Study
An investigation into ways to rebalance CitiBike stations throughout New York City.
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As has been recently documented by the press, one of the major challenges that Citi Bike is facing is the rebalancing of their stations. As origins and destinations of Citi Bike trips are not necessarily symmetrical during the day, Citi Bike has been forced to constantly move bikes around the city, taking them from full stations and delivering them to empty ones. This problem is both financially expensive and frustrating for Citi Bike users: many people complain about either not finding bikes at their stations of origin or not finding empty spots when they arrive at their final destinations.

To study this problem we have created a series of visualizations which should serve as a starting point for further analysis.

First, we visualized the average activity for weekdays in October 2013.

Citi Bike Hourly Activity

As the above image shows, the activity hotspots remain pretty constant throughout the day, specially between 10am and midnight, with most of the activity centered around Union Square. In addition, we also see how both Grand Central and Penn Station become strong hotspots during peak hours. Of interest, though, is the sudden shift that occurs around 5am, with the activity hotspots switching from the East Village/Lower East Side area, to Grand Central and Penn Station. This is probably due to the fact that during most of the night, compared to other areas, the stations in the East Village/Lower East Side continue to have high activity, but during most of the day, and specially during peak hours, they are not as active as the stations around Union Square or Grand Central and Penn Station.

Citi Bike Hourly Balance

Next, we visualized overall patterns of origins and destinations. As the above image shows, the big hotspots of imbalance are mostly located around the East Village, Lower East Side, Midtown East and West and Union Square. However, the variation of these hotspots throughout the day is pretty extensive and it's very difficult to detect smooth transitions apart from peak hours. Of note are a couple of big "jumps" between origins and destinations, one of them around 1-2pm on the East Village/Lower East Side and another one around 5am also in the same area.

 

We also created a series of imbalance matrices (by hour of day) for every single station on the system. Again, using the same data as the animations above, this first matrix (Citi Bike Hourly Balance) clearly shows how the big imbalances happen (as expected) mainly between 6am and 10am (morning peak hour) and between 4pm and 8pm (evening peak hour). However, there are some stations whose imbalance starts and ends earlier, like 8th Ave. & 31st Street, W 33rd Street & 7th Ave. and W 41st Street & 8th Ave. (more origins than destinations starting around 2pm). In addition, this matrix also shows that not all of the stations suffer from big imbalances during peak hours. Indeed, stations like E 31st Street & 3rd Ave or E 32nd Street & Park Ave. barely have any imbalances during peak hours. You can download a high-res version of this matrix here.

Imbalance matrix normalized by hourly activity

Furthermore, as not all of the stations have the same level of activity, we produced two more matrices, both showing station imbalance, but this time comparing it to the overall hourly activity for each station. The first one (Imabalance matrix normalized by hourly activity) shows the imbalance as a percentage of the activity for that hour. Hence, the great imbalances appearing late at night, when there are fewer trips and there's a higher chance of having all of them as origins or destinations. However, it is still interesting to see that there are higher imbalances during the morning peak hour than during the evening one, as a percentage of the overall activity.

Activity and imbalance matrix

The second matrix (Activity and imbalance matrix) shows the imbalance as colors and the overall activity as brightness, so we can see how in the hours between the peak times there's still a lot of activity but it is mostly well balanced. In addition, we can see how late at night (imbalanced as it may be) there's still very little activity. Finally, we can also see some outlier stations with a lot of activity and still pretty imbalanced: for example, in the morning 8th avenue and 31st street, 17th street and Broadway, Lafayette and 8th street, and Pershing Square (north); and in the evening 8th avenue and 31st street, 41st street and 8th avenue and again Pershing Square (north). You can download both of these matrices at high res here and here.

Imbalance Hotspots - A.M. Peak Hour

Finally, we have created hotspot maps for both the AM and the PM peak hours. As you can see from the maps below, Citi Bike activity closely matches what we would expect to see in New York: the AM peak hour map shows people leaving residential neighborhoods (Lower East Side, East Village, Chelsea and Hells Kitchen) and arriving at Midtown East and the Financial District, and the PM peak hour map shows the reverse. To note, however, is the fact that these two maps are not completely symmetrical, meaning that there are certain trips that happen in the morning which do not have their counterpart in the evening, and vice versa. Also, there are some stations that while being inside imbalance hotspots do not show that large of an imbalance. These stations have been outlined on the maps and should be further studied. You can view high-res versions of these maps here: AM and PM.

Imbalance Hotspots - P.M. Peak Hour

 

 
Urban Design Event Series - Activity Mapping

As part of the Urban Design Event Series (5 Borough Studio, Summer 2014), Juan Francisco Saldarriaga presented the lecture Activity Mapping, at the Graduate School of Architecture, Planning and Preservation, Columbia University.

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Turning Cryptic Data Into Beautiful Digital Mosaics
Feb 10, 2014 — The Creators Project

Advanced Data Visualization Project written up by Johnny Magdaleno on The Creators Project

"Since technology is responsible for growth in the world’s collective knowledge, it also shares the responsibility of categorizing that knowledge into easily digestible bites. Because what’s the use of this glut if it can’t easily be understood? And in order for data to have the largest possible impact, doesn’t it make sense for it to be understandable by researchers and blog-readers alike?

This conflict is one of the main issues breathing life into the Advanced Data Visualization Project (ADVP), a data analyzation project now in its second year at Columbia University. Birthed from a collaboration between international newswire Thomson Reuters and Columbia University’s Graduate School of Architecture, Planning and Preservation (GSAPP), the ADVP is looking to make intricate systems--like neurons, international port logistics and library catalogues--both easily readable and stunningly beautiful."

Visit the link below to find out more:

http://thecreatorsproject.vice.com/blog/turning-cryptic-data-into-beautiful-digital-mosaics

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Columbia University and Thomson Reuters Launch Advanced Data Visualization Project
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Jul 02, 2012 — Thomson Reuters

Thomson Reuters announces our new initiative:

"Columbia University and Thomson Reuters today announced the launch of the Advanced Data Visualization Project (ADVP) based at Columbia's Graduate School of Architecture, Planning and Preservation (GSAPP). The initiative, sponsored by Thomson Reuters, will facilitate research into data visualization and its implications for academia and industry in a world increasingly awash with data."

Visit the link below to find out more: http://www.reuters.com/article/2012/07/02/idUS122949+02-Jul-2012+HUG20120702

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Terre Natale: Exits Part 2
A panoramic multi-media installation which was on view at the Cartier Foundation in Paris, France as part of “Elsewhere starts here.”
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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. Exits, 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, geogoded, 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.

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Jumping The Great Firewall
This project visualizes censorship and online expression on the twitter–like micro–blogging platform Weibo.
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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.

Use of the Internet in China is policed — watched over, censored, and punished — by a human and technological program that has been nicknamed 'The Great Firewall'. The aim is to keep politically unacceptable or "sensitive" content (words and articles about the Tiananmen Square massacre, for example) invisible to Chinese Internet users. Twitter and Facebook are largely blocked, as are many news outlets and human rights web sites; web searches are seriously curtailed; sensitive words are blocked; and online postings and other content is routinely removed, blog posting removed. For many Chinese users who wish to access blocked web sites, the only option is a Virtual Private Network (VPN), a virtual leap over the Great Firewall.

We examined a different strategy that has emerged in Weibo blogging, where users can insert images directly into their postings, without links. 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. Visualized here are many such deleted posts from September 8th to November 13th, in 2013.

Research for this investigation was conducted in collaboration with a team at the Spatial Information Design Lab and the Brown Institute for Media Innovation, in partnership with Pen American Center and ProPublica. The ProPublica article, called China's Memory Hole: The Images Erased From Sina Weibo" uses a similar methodology to ours.

Research for this investigation was conducted in collaboration with a team at the Spatial Information Design Lab and the Brown Institute for Media Innovation, in partnership with Pen American Center and ProPublica. 

 

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Port to Port
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.
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A visual exploration of energy shipping routes around the world.

90% 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.

In collaboration with Thomson Reuters Research Unit.

U.S. and foreign ports by amount of imports.

 

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