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If you are like me and watch an unhealthy amount of professional basketball, it would behoove you to check out Stats.NBA.com and spend the next, oh, 8 hours or so poring over “advanced metrics.” New statistical categories like TS% (True Shooting Percentage), PIE (Player Impact Estimate), and EFF (Efficiency Rating), have been created in the past few years to explain the game in ways plain ol’ points, rebounds, and assists cannot.
The “statistical revolution” in basketball was started by nerds, embraced by bloggers, co-opted by front offices, and is now packaged in friendly charts and graphs. The site is comprehensive, easy to use, and pretty to look at. Check it out.
This collection of motion infographics from Bloomberg is pretty amazing. Each takes a single, complex issue and explains it using brief, animated infographic. Beyond simply being a visual expression of data, each video tells a story, leaving the viewer with a full understanding of the issue at hand. Granted, not everyone has the expertise (or budget) to employ motion infographics, but there are little lessons to be learned in each. Enjoy.
The U.S. Census Bureau Center for Economic Studies has long supported (for the past ~5 years) an online system for pulling area-based employment and residence data using a visual map-based selection tool called OnTheMap. This software is fairly intuitive and fun to use, but can also be quite useful in exploring a specific market or region to understand where workers live and work, and how that has changed over time.
OnTheMap is useful for more than work location, however. It’s a multi-layered mapping tool, with companion data on demographics, earnings, industry characteristics. We’ve also used it to identify exact metropolitan statistical areas and radius ranges, to find transportation routes, greenspace, and tribal and military lands, and to simply better understand a physical marketplace.
For years, organizations like the Census Bureau relied heavily on point-in-time estimates, tables of statistics and physical and static maps for data exploration like this. As new systems come online, are developed further, and improved over successive versions, our ability to access information from our desktops is not only facilitated but empowered.
Infomous is a dynamic and intuitive navigation solution – perhaps soon to pop up on websites you visit. Web developers for content-rich sites have integrated word cloud and tablet-style flip navigation over the past few years, but this is a solution that seems to combine aspects of both: reference triggers and dynamic script. The tool is currently available in preview/beta version through a relationship with the provider, but will roll out later this year, ready for embed. More info at Infomous – they have a demo up for world news, a version for sports news, entertainment news, science news. It’s easy to explore and find links to try.
Came across this lovely little infographic over the weekend, and I thought it was worth sharing. Behold The T-Shirt Lifecycle, a taxonomy of t-shirts based on age, use, and coolness. While it may be overkill, as a guy with a burgeoning t-shirt collection myself, I can completely get it.
There is an interesting round-up and comment discussion published at The Big Picture about models that visualize a hierarchy of intelligence. The images below also link through to their sources and related discussions.
The paradigm has traditionally been 1) Data 2) Information 3) Knowledge and 4) Wisdom. As data sources amass, and become more widely accessible through digital interconnectivity, does the model hold up? Are the definitions of each of these “levels” evolving? To visualize this model for various applications, what story should we try to tell? Do the stories below seem relevant (the story of how organization increases, or the story of how data is produced, consumed, then personalized)? Does the model only serve as an explanatory framework, or can it be applied to strategies for learning; for communications? It’s interesting to think about these questions, and to consider the evolution of this model, and various visual approaches to its application, over time.
Okay, this one’s a little obtuse… 🙂 Check the article too, whew!