Building a new software tool as web application is a great way to let lots of people have access to your creation without requiring them to install anything on their computer. Just deploy your application on a server, share the URL, and you’re done. It’s cross platform, and it’s installation-free. It’s become the default architecture much of our modern software.
But sometimes you really do want a desktop app. Perhaps you want your software to run without internet access.
This post is to share a bookmarklet that I created to help ease access to articles behind publisher paywalls. If you try to access an article and get blocked by a publisher, this bookmarklet makes it easy to search the UNC Library to see if you can get it through one of their subscriptions.
Suppose you are browsing a publisher’s website and you get a “you must pay” message. No problem!
Maps of election results are a staple in the US during campaign season. They appear in countless newspaper articles, TV news stories, and blog posts. Given the state-by-state nature of our electoral presidential election system, these maps are very valuable in understanding the state of an election race.
They have a problem, however, that is common to many maps. While maps represent area quite well, they can be deceptive when the data being visualized corresponds to something that doesn’t correlate well with area.
While there are a variety of Javascript libraries available for creating visualizations, the most widely used is D3.js.
D3 stands for Data-Driven Documents, and at the core of D3 is a programming model in which users join data elements to document elements. These are often SVG elements, but D3 can really be used for any kind of data-driven DOM manipulation. I instruct my students on the basics of D3.js as part of the Visual Analytics course which I teach every fall.
Risk is a difficult concept, in part because of the many ways it is measured. Interpreting specific numbers can be unintuitive even for people who do it every day, leading to critical decisions being made based on faulty interpretations of evidence.
This is a place where data visualization can play a crucial role. A recent article in Science makes a similar point, with a graphic example of how to help people understand that even “accurate” medical tests can be misleading.
[caption id=“attachment_631” align=“alignright” width=“150”] SciPy 2015 Conference[/caption]
In some of my recent research work, I’ve been thinkg about ways to expand the typical exploratory visualization process to incorporate more rigorous statistical assessments of the underlying samples being visualized. The power of visualization is that it can help people make quick inferences about complex data. Of course, this is also the danger. Quick inferences often overlook subtle—and often invisible—issues like selection bias or confounding factors.
Aaron Reiss published a really interesting article comparing the design of metro ticket machines used by the MTA (in New York) and BART (in the Bay Area). The MTA ticket machines are an icon of design and, for me, bring back good memories of life in the New York area. How are they different from BART machines? And why? This is a fun read that dives into some of the history and context that led to the design decisions.
[caption id=“attachment_488” align=“alignright” width=“150”] New York Times: For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights[/caption]
With a move to a new house and a new class being developed, I’m a bit behind in posting to this blog. However, I wanted to make sure I eventually posted a link to this article from over the summer in the New York Times. It provides a nice picture of what the art of Data Science looks like in 2014.
[caption id=“attachment_454” align=“alignright” width=“300”] From the New York Times. Distribution of marathon completion times with red lines marking hourly milestones. Click the image to visit the original article.[/caption]
An intersting article on the New York Times’ new data-based venture The Upshot highlights a study from researchers at USC, Berkeley, and the University of Chicago in which millions of marathon results were gathered together and plotted as a simple histogram.
The result?
This TED talk, by Dan Ariely, is one I first saw a long time ago but happened to stumble across again this morning. Dan is the author of Predictibly Irrational, which is an easy-to-read book along the same lines as this talk. So if you like the presentaiton, I recommend the book. The lessons from these types of studies are important for visual communication. We often feel that giving people more information will make it easier to make the right choices.