Thursday September 9, 2010

April 15, 2010

The underlying problem is that design is a holistic discipline while data-analysis, applied dogmatically, is a reductive discipline. When the two coincide, serious friction can ensue. But far from vowing to never interact, these two disciplines need each other tremendously. The designer brings perspective that helps to organize experiential systems at all scales, while quantitative metrics are key for validating decisions. The problems arise when analysis is treated as the primary driver for invention—that’s like setting a measuring tape on a drafting table and expecting it to design spectacular architecture—rest assured, the genius is not in the tape. …

The interplay of all disciplines (engineering, design, research, marketing, sales, QA, product, legal, customer care, etc.) is where the magic happens. Metrics are an absolutely critical interface between disciplines, but when wielded and controlled by only one discipline they can greatly limit the potential of the others.

Tom Chi
Co-Writer and Co-Illustrator, OK/Cancel

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Source: Bowman vs Google? Why Data and Design Need Each Other

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December 12, 2009

I believe that good design is good communication, finding the best way to communicate an idea or a concept. This allows designers to take a huge part in making change happen in the world. That’s some of the appeal that data visualization has for me—being able to show something, to tell a story that is hidden in raw data. … one must be as concerned about the data being shown as with the intention of telling its story. Sometimes, it takes a certain degree of aesthetics in order to draw the audience into your story. Other times, you need to keep away from aesthetic approaches for the best result.

Pedro Monteiro
Art Editor

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Source: Interview with Dava Viz Star Pedro Monteiro by Brain Pickings

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October 20, 2009

If the data allows it, we like to break down information into a graphical hierarchy similar to poster designs: a larger motive or trend is visible at first glance, and more detailed information becomes clear on closer inspection. Furthermore, the design should reflect some of its content. The data does not always allow for this: many times a simple bar graph is best. That said, a design cannot exceed its content: bad data sets lead to bad graphics, however simple or conventional the design is.

Joris Maltha and Daniel Gross
Designers and Founders, Catalogtree

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Source: Catalogtree Interview by Greg J. Smith, Serial Consign

Via: Quipsologies

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September 4, 2009

The challenge of communicating the significance of numbers—and acting on them—is to find ways to bring them closer to people’s day-to-day experience.

Building intuition about numbers is different from shocking people with numbers.

A good statistic is one that aids a decision or shapes an opinion. For a stat to do either of those, it must be dragged within the everyday. That’s your job—to do the dragging. In our world of billions and trillions, that can be a lot of manual labor. But it’s worth it: A number people can grasp is a number that can make a difference.

Dan and Chip Heath
Authors, Made to Stick

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Source: The Gripping Statistic: How to Make Your Data Matter

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