Tagged: opendata

At Mobility Lab‘s recent hack day, WMATA released a copy of the GTFS data they use for their trip planner. The trip planner includes schedule data for a total of 19 different transit agencies. GTFS, General Transit Feed Specification, is a collection of files that together form a complete description of all the routes, stops, and schedules. WMATA released an animation of the data last November (see Maps in Motion: Telling Stories from Transit Data). With the GTFS data now publicly available, I wanted to try making my own animations.


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A few days ago I animated a day of Capital Bikeshare trips using a new Java program I had written in Processing (see Animating Data with Processing). I wanted the program to be flexible enough to allow people to customize for their own uses, so I put it to the test myself by making slight modifications to its display.

For the first customization, I wanted to zoom into Dupont Circle. It turns out that at this scale, drawing a frame every 60 seconds means bikes disappear from view without giving an impression of movement. So, I had to slow down the speed. The video below samples the data every 5 seconds (12 times slower than before), so you can follow individual bikes. The video displays 30 frames per second. The data is from October 5, 2012, from 8am to 8pm.


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bixiHow did you celebrate International Open Data Day? Bixi Montreal contributed by releasing a summary of data for a single day, at dataholic.ca/odd/bixiday.xlsx. This is the first time the public has gotten access to their data. I added them to my collection, and can now offer the Bixi Montreal Trip Visualizer.

Their data included two matrices of station-to-station trip totals, for the AM and the PM. To simplify the data, my visualizer combines the two. I hope to add a feature later on to differentiate between the two data sets. I do not know which day the data is from.

Montreal has 410 bikesharing stations, making it one of the largest systems in the world. By comparison, Capital Bikeshare in the DC metropolitan area has 199 stations, and is the largest in the USA (until New York City’s system makes its debut). Montreal was the first city to use the Bixi system, starting in May 2009. Bixi now provides bikesharing facilities for 10 cities, including the other 3 that I’ve done trip visualizers for: Washington, DC, Boston, and Minneapolis-St Paul. » Continue Reading…

arlingtonArlington County has released its own set of bicycle accident data. There were 227 incidents recorded from January 1, 2010 to December 31, 2012 (though the first recorded accident wasn’t until March 1, 2010). That’s 6.3 reported incidents a month. I’ve made a map for them, the Arlington Bicycle Accidents Stat Mapper. It’s the same program as the DC Bicycle Accidents Stat Mapper.

I did not combine the two jurisdictions because the date ranges are different, and because the data formats were different.

Arlington’s map has 174 locations. The spot with the most accidents was Lee Highway at Fort Myer Dr, with 8 accidents recorded there. Clicking on a pin will show detailed information for all of the incidents at that location.

The source data has an “at” street and a “cross” street for each record. Some of them have a “landmark” field which is often used to describe the block number, and another field (3, actually, which I’ve combined) is sometimes used to describe the distance from the intersection. » Continue Reading…

Bicycle Counts Stat MapperLast June, DDOT and MWCOG counted bicycle traffic over an 8-hour period in 48 locations. I got a copy of the results, and converted the spreadsheet into a map. The Bicycle Counts Stat Mapper uses the same interface I created for the Bicycle Accidents Stat Mapper, but with a few new features added.

A total of 21,930 cyclists were counted. They also recorded the rider’s sex, whether they were on a sidewalk, whether they were wearing a helmet, and whether they were riding a Capital Bikeshare bike: 75% were male, 27% were on a sidewalk, 69% wore helmets, 5% were on CaBi.

The place with the most bike traffic was the 15th St cycle track, measured north of P St. It got just under 200 cyclists per hour (198.8 to be exact). Its busiest hour saw 355 cyclists go through. » Continue Reading…

statmapperWhen TheWashCycle blog reported on the Bicycle Crash Study 2010-2012, I was surprised to see the report didn’t include a map. So, I created a tool to view a map of the accident locations: the Stat Mapper.

I got a copy of the source data from DDOT. It covers January 6, 2010 to March 31, 2012. That period has 1,087 accidents in 744 locations. The report lists locations using text descriptions of the intersections. To convert into latitude & longitude coordinates for the map, I relied on Google’s geocoder. These results aren’t always accurate, especially if the text isn’t easily understood, like one accident that was recorded at “FBI:INTERSTATE 295” (the geocoder placed that at the center of the city, but I manually moved it to 3rd & E NW).

By default the map shows a pin at every accident location. When you hover over a pin the header will show the total number of accidents there, as well as the total number of fatalities and injuries, and the number of vehicles and bicycles involved. You can click on the pin to get a full listing of all the accidents at that spot. The darker the pin, the more accidents at that location. The spot with the most accidents, nine, was at 14th & U NW. » Continue Reading…

orangelineThe Metro Trip Visualizer lets you study Metro traffic patterns, plotting results on a map. Look familiar? It’s the same tool I’ve used for the CaBi Trip Visualizer, the Hubway Trip Visualizer, and the Nice Ride Trip Visualizer. They’ve all been consolidated into a single interface.

While Metro doesn’t regularly post trip history data, they did release a chunk via their PlanItMetro blog: Data Download: Metrorail Ridership by Origin and Destination. The data is actually just a summary of the trip history data, giving station-to-station totals. Though they divide the data by time periods (AM peak, midday, PM peak, evening, and late-night peak), my tool considers only the totals. » Continue Reading…

Metro Trips Visualized

nicerideLet’s look at trip history data for the bike-sharing system in Minneapolis and St Paul. I’ve adapted the CaBi Trip Visualizer for Nice Ride Minnesota. They’ve released a seven-month chunk of data, covering April 4, 2012 to November 4, 2012. It was easy to adapt the program for their data. So, voilà: the Nice Ride Trip Visualizer.

Click on any station to see the stations that form the most station-pairs. Not being familiar with the Twin Cites, I wanted to see the entire system’s network. To do that, hit the “1” key to select all the stations visible on the map. I was surprised to see the most prominent station-pair spans the Mississippi River, from Kolthoff Hall to the Social Sciences building, both on the campus of the University of Minnesota. These trips must use the Washington Avenue Bridge. » Continue Reading…

A new round of trip history data has been made public by Capital Bikeshare. I’ve created a new version of the CaBi Trip Visualizer for the 4th Quarter of 2012, covering October through December. Use the tool to analyze travel patterns for people using the bikeshare system.

475,736 trips were made in the 4th quarter. The bikesharing usage is highly seasonal, as ridership went down 25% from the 3rd quarter (the summer months: July, August and September). But compared to 2011’s 4th quarter, ridership is up 52%. Broken down by membership types, the number of rides by registered users went up 54%, and the number of rides by casual users went up 40%. Registered users are those who buy memberships for 1 month or 1 year; casual users buy memberships for 1 day or 5 days. » Continue Reading…

dccabiI love biking and mapping, so any chance to play with geo-spatial bike data usually results in a new little bike-data-mapping application. My latest analytical tool was made using Capital Bikeshare‘s data for the Washington, DC region. The CaBi Trip Visualizer uses the data from 2012’s 3rd quarter (the most recently-available) to create an interactive map. When you select a station, arrows point to the stations that most trips go to or come from. (See A Closer Look at Bikeshare Data for more details, and Looking at CaBi Stats with a Bubble Map for a different method of visual analysis.)

Hovering over an arrow or the station it points to displays a window showing the trips made between the two stations. The difference between the two directions is the “unbalancedness,” also shown as a percent of the total.

bostonhubwayI wanted to see how challenging it would be to adjust the program for bike-sharing systems in other cites, though Capital Bikeshare is the only one I’ve ever used. I looked at web sites for Paris’s Vélib’, London’s Barclays Cycle Hire, and Denver B-cycle, but couldn’t find any links for open data.

Boston’s Hubway doesn’t post trip data on their web site, but the Hubway Data Visualization Challenge made available data from a 14-month period (July 28, 2011 to October 1, 2012). Though the contest has ended, I created my Hubway Trip Visualizer. » Continue Reading…