Viz-Fest Day 3 – Data Visualization and Dashboards #MRX #NewMR


Live note-taking from Viz-Fest, November 2016. Any errors are my own.

Tom Schlak, E-Tabs, Data Viz for the Visually Impaired

  • Most important information visually displayed to achieve objectives and can be monitored at a glance, Charts, graphs, icons, mostly visual
  • How can data visualization be made accessible to someone who is blind
  • Viewing a musical score versus listening to a score, “seeing” a chart can’t be replicated
  • What are the alternatives, Maybe use speech assistive technologies
  • 5% of the world has some visual impairment, 11.5% for people over 50 years of age
  • Good designs benefit everyone even fully sighted users
  • Text and fonts – font size on screen nothing less than 12 to 16 points, Helvetica, Arial
  • Font styles more complicated, must consider legibility and readability, legibility is individual characters, readability is overall appearance including spacing and formatting, good fonts have better spacing, less fancy script, less detailed, filled lettering, less heavy, less thin, less serif, Use display fonts carefully because they aren’t accessible
  • Contrast – sometimes corporate colours are a problem but readability must come first, use an online tool like adobe color CC, let’s you choose colors that match your target color or complement, matters for typography too, forget white on yellow, yellow on red, grey on green
  • Clean user experience – avoid cluttered dashboard, eliminate non-data pixels like background images and watermarks, large logos, etc, think about data-to-ink ratio, avoid dark gridlines or over-labeling, don’t fill up backgrounds just because you can, gradients of grey can be difficult to differentiate, use colors like red and green appropriately, only highlight what must be highlighted, flatten the design by removing shadows and 3D elements that make a flat image look shiny
  • Eg Microsoft logo went from shiny colored circle to four simple boxes
  • What about color deficiency, blindness – 8% of men and .5% of women have deficiencies, the worst forms can distinguish 20 hues but people without can see about 100 hues
  • Avoid red green charts as this can hide the data
  • Traffic light indicators are common, red green yellow, and should be used with caution, consider using shapes as well, arrows, checkmarks, faces, and maybe use them only for one state, just the positives or just the negatives
  • Use cross hatching or fill patterns so you don’t rely just on color
  • Use Colblinder online to test colors, light colors can lose their differentiation, text labels will help, try also ColorBrewer online
  • Much of this applies to good design anyway
  • Is it still beautiful is someone can’t see it? Communicate to everyone

Marta Blankenberger, redaviZ, Data Driven Infographics

  • Infographic is visual representation of data to share information quickly and clearly
  • Need to think about position, size, shape, color
  • Icons help us understand and interpret information
  • Combine a doughnut chart with an icon, or combine a bubble chart with a map behind it
  • Masking – cover or uncover part of a chart but placing a shape in front of it, try that with charts, grey out a section or tone down the color of part of it
  • Combine icons, put stars over circles to mask different areas
  • Try using an arrow as the bars in a bar chart, just paste the image into the bar
  • Try putting a grey bar behind the bars to represent the maximum of the bar
  • Try using copied icons as the bar (e.g., 5 stars, 8 stars, 3 stars), you can use masking to turn 5 out of 10 into 5.3 out of 10
  • Use conditional formatting of data labels, change the color/shape/size of labels if they are less than a specified value, or put checkmarks as the data point
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