Check out these papers, videos, blogs and more from IBM’s visualization luminaries.
When companies can analyze big data, they benefit. Visualization can play a vital role in making sense of your big data. This paper by T. Alan Keahey, Ph.D., IBM Visualization, Science and Systems Expert shows you how.
Knowing how to use visual properties effectively has a powerful effect on the accessibility and utility of your visualization.
The indispensability of visualization (YouTube, 00:10:23)
IBM visualizations luminaries Graham Wills and Frank Van Ham sat down at the 2012 IBM Information On Demand conference to discuss the indispensability of visualization.
The goal of visualization is to make the complex intuitive and as simple as possible. IBM visualization luminary Graham Wills provides suggestions for how to do this.
No need to call in the mathematicians. IBM visualization luminary Graham Wills is merely explaining how visualization design and how different visual features work together.
The most common framework for embedding visualizations is a rectangle in the overall display, with other controls and information arrayed outside of the rectangle. Learn why Alan Keahey calls this Visualization in a Box and how you can get more of the interaction inside the box, thereby manipulating the information directly rather than through external controls.
After you have determined the purpose (the why of a visualization), you can start thinking about what you want to visualize. The task is to include the relevant data (that which you know is useful) and to leave the rest out. Noah Iliinsky, IBM Visualization Luminary, offers tips for figuring all this out.
What makes a successful visualization? IBM visualization luminary, Noah Iliinsky, explains the four pillars of visualization and why they matter.
Because information visualizations are subjective carriers of a particular message, you can apply communication theory to your design. IBM visualization luminary Frank van Ham explains how.
The hardest challenge in dealing with 'big data” is finding ways to refine it into useful information. IBM visualization luminary Frank van Ham shares his ideas for how it can be done.
IBM visualization luminary Frank van Ham reflects on how Many Eyes came to be and some of the paths the original research team followed.
How do you visualize many variables all in the same format? IBM visualization luminary Graham Wills breaks down a visualization to show you how.
What makes a good visualization? Is it the quality of the presentation or something more? IBM visualization luminary Graham Wills answers these questions and others.
OLAP “locks” us into a data model. But, data doesn’t always have one definite model. IBM visualization luminary Frank van Ham writes about resolving this incompatibility.
A shift from being data-centric to being question-centric is needed in this era of big data. Eser Kandogan of IBM Research tackles the idea of “Big Questions” and how to answer them.
IBM visualization luminary Dr. T. Alan Keahey compares visualizations to another well-known technology that has evolved significantly over the last 100 years: the automobile.