Here's where we post periodic updates on what we've been up to at Fathom. Reflections on the interesting stories that emerge from our client work, side projects, after-hours rabbitholes, and other miscellaneous threads of inquiry.
Hot off the press—and just in time for the holidays—are two print projects that look at the six editions of Charles Darwin's, On the Origin of Species. Originally developed as an interactive piece, we decided to continue our tradition of producing and selling unique printed artifacts. And as always, all of the proceeds from this work will be donated to charities focused on education, science, music, art, food, and homelessness.
In my last blogpost, I showed some visualizations generated by usage data from our tool Mirador. These visualizations rely on the calculation of a "distance" between variables in a dataset, and Information Theory allows us to define such distance, as we will see below.
This new post is the continuation of a series of writings (1, 2) on discovering correlations in complex datasets. Some of the ideas I discussed so far have made their way into Mirador, a tool for visual exploratory analysis developed in collaboration with the Sabeti Lab at Harvard University and the Broad Institute. By visualizing "information distance" to construct a geometric representation of statistical correlation, I will describe the usage patterns within the interface of Mirador. Keep reading for the details!
A few weeks ago, we released No Ceilings 2.0 in conjunction with the annual Clinton Global Initiative (CGI) meeting. Along with refurbishing the design on the landing page, we created a new visualization optimized for an installation setting. The visualization measures the change—or lack thereof—of the gender gap in labor force participation over the last twenty years. In addition, we released country snapshots, which provide an overview of the status of girls and women in each country.
We've had an ongoing interest in activity data from projects with the Nike FuelBand (Year in NikeFuel and NikeFuel Weather Activity) to more recently with Fathom Watch Faces for Android Wear. This work has inspired me to track every place I've been and how I've moved between locations with the Moves app. With about twenty months of data on my hands I began parsing, analyzing and creating sketches.
In honor of Women's Equality Day, we released a new No Ceilings visualization exploring how disparities in wealth engender gaps in primary school completion. Girls from low-income households are often at the greatest disadvantage in their access to basic education, most predominantly in Middle Eastern and African countries. For all of the inequalities that exist in the U.S. school systems, there are millions of girls around the world who don't have the opportunity to graduate elementary school, let alone attend it.
As anyone who has recently taken a road trip can attest, there are a lot of places in the United States with very distinctive names. Many of us at Fathom are fascinated by geography and the subtle oddities around us, so it seemed only natural we create Place Poetry. The playful mobile application enables people to arrange strangely named cities into poems, while simultaneously plotting the location and distance of their journey.
We're excited to announce the launch of the Fathom Watch Faces, a collection of interactive watch face designs for the Android Wear collection, which is part of Google's Android Experiments. The experiments are designed to bring developers together on a common platform to push the capabilities of Android tablets, phones, and watches. We focused on using the internal components of the watches, such as their accelerometers and pedometers, to create delightful user feedback at every glance, and to really explore the information people can gain from a wearable device attached to their wrist.
I found Fathom through a data visualization course at college that was taught by a statistics professor, so my first exposure to information design was through the lens of statistical analysis. I spent most of my time in that class making sure the data was not misrepresented, and working through particularly challenging pieces of code. The more complicated the analysis or the code, the better I felt about the project, and I wanted that complexity to show in my end product. If the code worked and did something cool, then I was happy.