Visualization is the photograph presentation of knowledge -- portrayals intended to bare complicated details at a look. give some thought to the conventional map of the hot York urban subway approach, or a diagram of the human mind. profitable visualizations are attractive not just for his or her aesthetic layout, but in addition for based layers of element that successfully generate perception and new understanding.
This publication examines the equipment of 2 dozen visualization specialists who procedure their initiatives from a number of views -- as artists, designers, commentators, scientists, analysts, statisticians, and extra. jointly they show how visualization may also help us make feel of the world.
• discover the significance of storytelling with an easy visualization exercise
• find out how colour conveys info that our brains realize ahead of we're totally conscious of it
• observe how the books we purchase and the folk we go together with demonstrate clues to our deeper selves
• realize a style to the insanity of air go back and forth with a visualization of civilian air traffic
• learn how researchers examine unknown phenomena, from preliminary sketches to released papers
Nick Bilton, Michael E. Driscoll, Jonathan Feinberg, Danyel Fisher, Jessica Hagy, Gregor Hochmuth, Todd Holloway, Noah Iliinsky, Eddie Jabbour, Valdean Klump, Aaron Koblin, Robert Kosara, Valdis Krebs, JoAnn Kuchera-Morin et al., Andrew Odewahn, Adam Perer, Anders Persson, Maximilian Schich, Matthias Shapiro, Julie Steele, Moritz Stefaner, Jer Thorp, Fernanda Viegas, Martin Wattenberg, and Michael younger.
Read or Download Beautiful Visualization: Looking at Data through the Eyes of Experts (Theory In Practice, Volume 39) PDF
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Extra resources for Beautiful Visualization: Looking at Data through the Eyes of Experts (Theory In Practice, Volume 39)
Apply a Visual Representation Now that we have the data, we come to the task of deciding how to portray it. This means making decisions about what kind of visual representation of the data will aid viewers in understanding it. A visual representation is some kind of visual dimension that can change in correspondence to the data. For example: an XY graph is a simple visual presentation that maps an x, y data point in a two-dimensional plane. Map enough points, and an obvious visual pattern may emerge even if there is no immediately identifiable pattern in the raw data itself.
Returning to the questions listed previously, we now know what data we’re looking at and what the time frame is. This visualization is interactive: if the user presses the “Play” button at the top, dots along the timeline pop out to reveal important events that may have influenced the data one way or another (Figure 2-2). im/I2Gb. Question + Visual Data + Context = Story 17 Figure 2-2. The visual draws attention to important events that may have influenced the perceived newsworthiness of the candidates In addition to these cues, the user can draw on his knowledge of the presidential race to supply additional context to the data.
The author’s 2006 work email signature When dogear became an IBM product,* the tag explorer did not go with it, and I forgot all about it. When I found the tag explorer code by chance a couple of years later, I thought it was worth developing. The original tag explorer was intimately tied to dogear, and to the idea of tag clouds in general. I wanted to find a way to decouple the word-cloud effect from the whole idea of “tags,” since the pleasing and amusing qualities of the word cloud seemed generally accessible, while “tags” were familiar only to a technologically sophisticated crowd.