Snippet: Where the F**k Was I?

Posted: June 24th, 2011 | Author: | Filed under: Data Visualization, Snippets | 4 Comments »

James Bridle had an interesting reaction to the revelation that his iPhone was tracking his location: he made a book!

He describes his reaction to his phone’s data collection habits rather poetically:

I love its hunger for new places, the inquisitive sensor blooming in new areas of the city, the way it stripes the streets of Sydney and Udaipur; new to me, new to the machine. It is opening its eyes and looking around, walking the streets beside me with the same surprise.

His book is documented on his site and on flickr.


Snippet: The Popularity of Data Analysis Software

Posted: April 5th, 2011 | Author: | Filed under: Snippets | Tags: , , | 6 Comments »

We’re often asked what our tool stack looks like. Robert Muenchen over at r4stats has a study of the most popular data analysis software.

He looks at factors as varied as traffic on the language mailing lists, number of search results and web site popularity, sales, and finally surveys of use. For example:

mailing list traffic over time

It’s interesting to think which of these factors indicate greater adoption. Don’t let me spoil it for you, but R comes out looking good across the board.


Snippet: Science special collection on Dealing with Data

Posted: February 15th, 2011 | Author: | Filed under: Snippets | Tags: , , , | 2 Comments »

The February edition of Science offers a special collection of articles from scientists in a variety of fields on the challenges and opportunities of working with large amounts of data.

The overwhelming theme seems to be a need for tools, visualizations, and a common vocabulary for expressing, exploring, and working with data across disciplines.

Thanks to Chris Wiggins for the pointer.


Analyze data, save lives, win $3 million

Posted: February 5th, 2011 | Author: | Filed under: Snippets | Tags: , , , | 9 Comments »

Our friends at Kaggle are hosting the Heritage Health Prize. Launching April 4, the competition is seeking an algorithm that can predict patients at high risk for hospital admissions.

It’s difficult to do meaningful work with health data due to a variety of policy, legal, and technical challenges. The success of this contest will be something we can all point to as an indicator that we need to make more mindful decisions about how health data is managed and analyzed.

Who’s up for a dataists team entry?