Posts Tagged ‘paper’

Riding Through Mountains (of Data)

Tuesday, May 11th, 2010

(Here is the documentation for my thesis project at NYU’s Interactive Telecommunications Program. PDF version here.)

Riding through Mountains of Data:
Visualizations of Cycling

Robert Carlsen
Interactive Telecommunications Program
Tisch School of the Arts
New York University


This project attempts to describe the cycling experiences of several riders in New York City through a series of visualizations. Specifically, I am interested to discover if riders similar to myself share a common experience through which a sense of connection could be derived.

Cyclists were encouraged to record their travels using their personal mobile devices running Mobile Logger, a custom iPhone application.
Log data was uploaded by the application to an online database in near real-time during each ride. This data was analyzed and filtered to provide source material for the resulting visualizations and system “dashboard” at


Cycling, New York City, sensors, iPhone, visualization, mapping, tracking, logging, mobile, application, bicycle


Thesis Proposal – Draft

Wednesday, March 17th, 2010

Thesis Proposal Title
Where do we go now?

Thesis Statement
I will create a series of visualizations attempting to decipher the experiences of a large group of cyclists in New York City. The project has two principle components: data collection and analysis / visualization.

Personal Statement
Riding a bicycle provides me with a sense of self-reliance. It can provide transportation, fitness, employment and enjoyment. It’s faster than walking and more maneuverable than driving. In dense city congestion it can be faster than mass transit. However, we’re generally more exposed to the elements and danger than other traffic. What does this experience look like? How could it be recorded? Mobile sensors reflect a personal experience in a way that fixed sensors can only infer. Focusing on personal mobile devices as nodes in this network provides a priority on the experience of individuals.

What could we learn about ourselves and our world if there was a ubiquitous network of sensors collecting data about the environment as we experience it? Would analysis and visualization reveal trends and patterns in the aggregate behavior of participants in the network?

Personal Environmental Impact Report (UCLA Cens)
Flight Patterns,
Copenhagen Wheel (MIT Sensible City)
CitySense (Sense Networks)
Beautiful Data. Segaran & Hammerbacher. O’Reilly Media. 2009.
Open Data Consortium Project,

Work Description
GPS-enabled mobile devices are becoming prevalent enough to use them for large-scale personal data collection. The data collection portion of this project will utilize a mobile logging application (initially iPhone and Android ) to record each rider’s experience. The application will upload data to a server for storage and later analysis. To facilitate ride data, I will organize a one-day event (“Log your ride to work day”?) or piggy-back on an existing event (critical mass, charity ride). Alternatively, I may organize a proof-of-concept event with a smaller group over a longer time, perhaps a week.

Post collection, I will analyze the data looking for relationships and trends among riders. This analysis will be critical for the eventual visualizations. I have an initial set of questions which I’m looking to answer: How many other riders are are near another rider? How far apart are they? How fast are they traveling? Respectively? How smooth is the ride? Are they rocking? Do they lean to one side? Do several riders experience similar conditions at the same place and time? Where do riders go? Where do they originate? Where do they congregate?

Visualizations of this data derive from further questions. What does a group ride look like? What if location was stretched along a time axis like a ribbon? My overarching goal with this project is to make these possibly abstract images be meaningful to uninitiated viewers.

The end product will primarily be this series of static and interactive visualizations using the collected data. Additionally, I’m aiming to publish the project’s process in the spirit of open source. This includes publishing the collected data for other analysis, releasing the logger application source code, documenting collection methods and describing the visualization process. Hopefully, this will enable other people to extend and augment the work in ways I haven’t envisioned.

motivations: karma

Thursday, December 3rd, 2009

[written for Media Economics & Participation at ITP]

Slashdot users are seeking karma. However, gaining positive karma at Slashdot is just a means to an end; Slashdot users are seeking (limited) power and status among their peers in the form of fleeting moderator access for the vibrant comments component of the highly active, technology-focused news aggregation site. Moderators are chosen from among the registered users using a somewhat obscure algorithm which incorporates each user’s karma rating (a scale of Terrible, Bad, Neutral, Positive, Good, and Excellent), length of membership and randomness. Selected moderators are given special status and 5 mod{eration} points with an expiration window of three days. The moderation status ends when the points have been used in the act of moderating comments or have expired.

The moderation system has been borne out of necessity as the Slashdot community has grown large, bringing the signal-to-noise ratio down and decreasing the satisfaction in reading the raw comment threads. “Flamebait” and “trolls” contribute little more than instigation for starting arguments and fights among the users with typically strong opinions on matters which usually appear on Slashdot. Rob Malda, founder of Slashdot, explains this phenomenon on the Slashdot FAQ: (more…)