Design, Math, and Data: Lessons from the design community for developing data-driven applications by Dean Malmgren.
From the post:
When you hear someone say, “that is a nice infographic” or “check out this sweet dashboard,” many people infer that they are “well-designed.” Creating accessible (or for the cynical, “pretty”) content is only part of what makes good design powerful. The design process is geared toward solving specific problems. This process has been formalized in many ways (e.g., IDEO’s Human Centered Design, Marc Hassenzahl’s User Experience Design, or Braden Kowitz’s Story-Centered Design), but the basic idea is that you have to explore the breadth of the possible before you can isolate truly innovative ideas. We, at Datascope Analytics, argue that the same is true of designing effective data science tools, dashboards, engines, etc — in order to design effective dashboards, you must know what is possible.
As founders of Datascope Analytics, we have taken inspiration from Julio Ottino’s Whole Brain Thinking, learned from Stanford’s d.school, and even participated in an externship swap with IDEO to learn how the design process can be adapted to the particular challenges of data science (see interspersed images throughout).
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If you fear “some assembly required,” imagine how users feel with new interfaces.
Good advice on how to explore potential interface options.
Do you think HTML5 will lead to faster mock-ups?
See for example:
21 Fresh Examples of Websites Using HTML5 (2013)
40+ Useful HTML5 Examples and Tutorials (2012)
HTML5 Website Showcase: 48 Potential Flash-Killing Demos (2009, est.)
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