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Team #16

June 26, 2011

Data viz project title

  • Pathlist

Brief description

  • An iPhone app that draws multiple paths of different potential bike routes over a map of San Francisco. The elevation of the different route segments are shaded in different colors to represent how steep of climb the hills are, and, uniquely, the segments are colored by incline only in the direction of travel. By showing multiple routes at the same time, the hills are visible and your desired type of of ride to your destination can be determined.  Do you want to climb hills or ride around them? Now you can see what your route looks like before you go.

Team members names and affiliations

  • E.O. Stinson
  • Steffen Frost
  • Julia Klein
  • Kathleen Kegaarn

Datasets used

Data.SF street data (found via InfoChimps), uploaded to: http://www.factual.com/t/huU9fQ/SF_Bike_Routes_with_autoID

Software used

Xcode

APIs used

Factual iPhone Framework/iPhone SDK

Work done with the dataset before the event (describe if any)

None

Screenshots and/or video of the results


Link to the result (if applicable)

https://github.com/pathlist/pathList

Team #6

June 26, 2011

This project is a detailed analysis of how low- and high-performing schools have behaved over time. We analyzed these groups under the lens of teacher experience, charter school percentage and raw performance scores.

Team Member Names: Shan Lu, Sameer Farooqui, Jon Bender, Mauricio Vacas, Hareesh Ganesan

Affiliation of Team Members: Accenture Technology Labs, Duke University

Data Sets: http://www.factual.com/t/mEtm9G/US_Schools_Merged
http://www.factual.com/t/S3CN6w/2006_California_Academic_Performance_Index_Growth
http://www.factual.com/t/HZUd6z/2009_California_Academic_Performance_Index_Base 

Software Used: Python, Excel, Tableau, Photoshop

APIs Used: Factual

Work Done Before: Downloaded API data and uploaded to Factual

Link: http://i.imgur.com/hh8JR.png

Team #19

June 26, 2011

Marvel Universe Social Graph

Brought to you by team Xavier Institute for Higher Learning, X-Maps analyzes damage from leaked professional and interpersonal connection information centered on a social network of heroes from Earth-616 which extends across the multiverse.

The final results are posted here.

Data set used: Marvel Universe Social Graph

Team members (no previous affiliation):

  • Kai Chang, data morpher
  • Tom Turner, Gephi explorer
  • Jefferson Braswell, network analyst
Software used:
  • Google Refine and Python for data cleaning and transformation
  • Gephi for data visualization and analysis
  • Seadragon export for interactive web visualization
Work prior to event:
  • None. We used a dataset specifically for the competition.

Team #4

June 26, 2011

Project title: UFO Siter

Description:

Vision

This website plots UFO sighting data onto a map of the U.S. and allows the user to interact with it in various ways. A visitor to the site can see all sightings for all dates, and search for specific sitings by location –“Wichita, KS”, or “Whichita” or “Kansas” for example– or choose from a drop-down menu of State names and saved locations. Clicking on any sighting data point will pop up the full sighting record from the database. Media Search panel preferences allow this sighting’s record details to automatically generate a Search listing from YouTube or Google, and allow the visitor to modify the search terms and rate the search results for relevance. Time line data along the bottom allows the visitor to search for sightings by date, date range, or see a chronological “movie” of sightings as they occurred. Finally, the visitor can enter a new sighting record, ideally with photos and/or video of the sighting if they have any. “Community” aspects of the website (top nav) allow the visitor to read more about sightings and connect with others interested in the subject.

Implemention

Map with location of 1000 UFO sightings in the U.S.

Team members names

Brian J Sherman: www.brianjsherman.net, @clarityinfo, me@brianjsherman.net

Sjors Provoost: sprovoost.nl @provoost sjors@sprovoost.nl

Mark M. Muskardin: http://www.linkedin.com/in/markmuskardin, markmuskardin@gmail.com

Affiliation of team members

Met on LinkedIn prior to event.

Datasets used:
UFO sightings from Infochimps:
http://www.infochimps.com/datasets/60000-documented-ufo-sightings-with-text-descriptions-and-metada

Geonames list of U.S. cities and coordinates:
http://download.geonames.org/export/dump/  (US.zip)

Software used:
Ruby on Rails
MySQL
Google Maps API
Heroku
(Github, TextMate, Photoshop)

API’s used:
We downloaded the datasets. We used Google Maps API to plot.

Work done with the dataset before the event:

None.

Screenshots: (from presentation)
Vision:
Vision for UFOSiter

Implementation so far:
Implementation for UFOSiter

Process:
Process for UFOSiter

Link to the result:
http://bit.ly/UFOmap
Source: https://github.com/eaturspinach/ufo-mashup/

Team #10

June 26, 2011
by

Uber Shady

Where are Uber cabs taking people in the city? How many of them frequent the Tenderloin?

Brandon Liu, Zach Margolis, Diogo Monica, Billy Roh, Ian Wong (from Square)

Dataset used: Infochimps Uber GPS logs

Software used: node, d3, polymaps, processing, sqlite, (python, ruby and r for data manipulation)

No work was done with the dataset before the event. In fact, we switched ideas three times yesterday😛

Two screenshots:

http://dl.dropbox.com/u/1047237/Screen%20shot%202011-06-26%20at%2012.51.59%20PM.png

http://dl.dropbox.com/u/1047237/Screen%20shot%202011-06-26%20at%2012.05.07%20PM.png

Team #17

June 26, 2011
by

Parkalator

The real-time query and display of parking meter availability and price within San Francisco.

Team
Zac Bowling
Trey Doig
Steve Salevan
Julie Silverman
Vishal Verma

Datasets

Infochimps (SF Parking Meter)

SFPark

SFgov.org (neighborhood shape data)

APIs

SFPark

OpenLayers for OpenStreetMap

Geoserver

JQuery

SocketIO

Nginx

Data Massage

Particular points of pain: everything realting to GIS.

Check it out!

Team #1

June 26, 2011
by

CuriousSnakes

Remember back when you were a kid? You asked questions. You asked so many questions that your mother had to try very hard not to snap at you. What happened now?

Well, some adults are still curious fellows who asks questions. Just they don’t ask their mother any more. There’s something better now: the internet.

This visualization is a celebration of the sometimes fascinating, sometimes dull, and the sometimes outright disturbing questions people ask. Beware, the questions are uncensored!

Team members:

Fravic Fernando (U. of Waterloo)
David Ma (U. of Waterloo)
David Townsend (loyalize.com)
Lisa Zhang (U. of Waterloo, ContextLogic, dataInColour.com)

Datasets:

AOL Search Queries

Software:

Javascript, Processing, Python, Tornado (web server), R

API:

Work done with dataset before the event:

None

CuriouSnakes

Result:

Play with CuriouSnakes