It was about five years ago when I got into visualization. Before I actually made anything, I read books and guides that made suggestions and preached a handful of design principles, but when it was time to make a data graphic for publication, I didn’t know what I was doing. Theory is great. Being able to apply it to your own data is better.

Back then — which seems like forever but isn’t actually that long ago — there weren’t many practical tutorials or books on how to visualize data. Visualize This is the book I wish I had when I was starting out. A steady foundation and an introduction to what’s out there, written to my old self.

There’s still so much more to visualization though. There are different points of view to explore, new software and methods to try, and growing data sources to play with.

That’s where FlowingData memberships come in. Having great sponsors lets me write tutorials and longer articles occasionally, but memberships will allow me to write more and perhaps bring in others’ expertise from time to time.

Here’s what you get with FlowingData membership:

• Monthly Tutorials: How to make and design publication-level data graphics.
• Downloads: Source code and files to use with your own data.
• Guides and Resources: Design principles and the best places to learn them.
• Curated Links: Hand-picked links from around the Web that focus on the how of visualization.

Those who have Visualize This will recognize the style of the guides and tutorials (first members-only tutorial coming soon after this post). You can also check out past tutorials for a taste. Long-time readers will notice a new layout that’s easier to follow, and writing online lends itself better to more code-heavy projects.

All this for the introductory price of $25 per year — less than a coffee a month. I’ll also throw in a warm, fuzzy feeling from directly supporting an independent FlowingData. Your support helps ensure that the lights stay on, hopefully for years to come.

Become a member.

UPDATE: Paypal is acting up. Looking into it now.

UPDATE 2: Seems to be going okay again. It might take a couple of tries due to your awesomeness.

UPDATE 3: I think most of the kinks have been ironed out, but if you can’t log in for some reason, please email me at nathan [at] flowingdata [dot] com. Thanks for the support, everyone.

From Yanni Loukissas of the MIT Laboratory for Automation, Robotics, and Society, comes the story of the Apollo 11 lunar landing told via multiple time series running in parallel and the back and forth between astronauts and mission control.

The Apollo 11 visualization draws together social and technical data from the 1969 moon landing in a dynamic 2D graphic. The horizontal axis is an interactive timeline. The vertical axis is divided into several sections, each corresponding to a data source. At the top, commentators are present in narratives from Digital Apollo and NASA technical debriefings. Just below are the members of ground control. The middle section is a log-scale graph stretching from Earth (~10E9 ft. away) to the Moon. Utterances from the landing CAPCOM, Duke, the command module pilot, Collins, the mission commander, Armstrong, and the lunar module pilot, Aldrin, are plotted on this graph.

Climax hits around the 4-minute mark. Too bad it doesn’t get to the one small step for man part.

Kyle McDonald and Arturo Castro play around with a face tracker and color interpolation to replace their own faces, in real-time, with celebrities such as that of Brad Pitt and Paris Hilton. Awesome. And creepy.

See Castro’s video of him doing the same thing, but with a different blending algorithm. His looks more like a maleable mask rather than a face substitution.

Grab the code on GitHub.

[Video Link via Waxy]

Jon Kleinberg, whose work influenced Google’s PageRank, is working on ranking something else. Kleinberg et al. developed an algorithm that ranks people, based on how they speak to each other.

“We show that in group discussions, power differentials between participants are subtly revealed by how much one individual immediately echoes the linguistic style of the person they are responding to,” say Kleinberg and co.

The key to this is an idea called linguistic co-ordination, in which speakers naturally copy the style of their interlocutors. Human behaviour experts have long studied the way individuals can copy the body language or tone of voice of their peers, some have even studied how this effect reveals the power differences between members of the group.

Now Kleinberg and co say the same thing happens with language style.

That’s why I just don’t talk at all. Introvert to the max.

[Technology Review]

Seth Stevenson, for Slate Magazine, covers cartographer David Imus’ hand-crafted wall map, which Stevenson calls the greatest paper map of the United States you’ll ever see.
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With the new year, many of you (myself included) and your employers resolved to be more productive this year. You are going to finish that side project. Learn that new language. Run that long distance. You are going to be all that you can be. Then you spent all day in front of the television yesterday while playing Angry Birds. Little did you know, productivity and Angry Birds go hand-in-hand.

Enter Productivity Birds, created and used internally by Stamen.

We’ve used these graphs as the simplest-possible visualization of how we spend our time so we know how we’re doing relative to the budget for a project. Operationally, the data output of these graphs feeds directly into an accrued revenue model that lets us predict our income earlier. The day/week granularity makes it possible to collect the data as a team without making everyone unhappy with management overhead, and the bias toward whole- or half-day increments helps stabilize fractured schedules (not for me, though—my time is probably the most shattered of anyone in the studio).

Calendar time is represented on the horizontal axis and time spent on a project is the vertical. The object of the game is to hit the bird, where a bird over the pig means a risk of losing money, and a bird past the big means a risk of finishing late. The stacked area chart on the bottom shows who has been or is working on the project.

The small app, built with Protovis, is available on GitHub.

[tecznotes]

While we’re on the topic of academic papers and how they’re linked, Johan Bollen et. al used clickstream data to draw detailed maps of science, from the point of view of those actually reading the papers. That is, instead of relying on citations, they used log data on how readers request papers, in the form of a billion user interactions on various web portals.

Maps of science derived from citation data visualize the relationships among scholarly publications or disciplines. They are valuable instruments for exploring the structure and evolution of scholarly activity. Much like early world charts, these maps of science provide an overall visual perspective of science as well as a reference system that stimulates further exploration. However, these maps are also significantly biased due to the nature of the citation data from which they are derived: existing citation databases overrepresent the natural sciences; substantial delays typical of journal publication yield insights in science past, not present; and connections between scientific disciplines are tracked in a manner that ignores informal cross-fertilization.

Cross-fertilization. Saucy.

Each circle represents a journal and edges represent connections between journals, according to Johan Bollen et. al’s clickstream model. Circles are color-coded by journal classifications from the Getty Research Institute’s Art and Architecture Thesaurus.

So you have most of the engineering and physical sciences on the perimeter, medical-related areas to the left, and liberal arts is that middle cluster. Statistics is towards the top left, mixed in with demographics, philosophy, and sociology. There aren’t many surprises in the clusters, but there are interesting, albeit weaker, links in the open spaces, such as religion and chemistry or music and ecology.

[PLoS ONE | Thanks, @drewconway]

From Autodesk Research, Citeology is an interactive that visualizes connections in academic research via paper citations:

The names of each of the 3,502 papers published at the CHI and UIST Human Computer Interaction (HCI) conferences between 1982 and 2010 are listed by year and sorted with the most cited papers in the middle. In total, 11,699 citations were made from one article to another within this collection. These citations are represented by the curved lines in the graphic, linking each paper to those that it referenced.

The interactive repsonds slowly to clicks and only works in Firefox for me, but it’s interesting to play around even if you aren’t familiar with CHI and HCI papers. It works better if you select one to three generations instead of all. Click on a specific paper and you get citations for that paper on the right (brown) and the papers that the selected cited on the left (blue).

Color-coding for categories, authors, or subject could add another level of meaning to this. For example, do we see the subject evolve? Do papers that focus on a certain subject site outside of the main topic?

[Citeology via infosthetics]