Design Principles for Data Visualization

  • Charts should be organized, have labeling, search, navigation systems, filtering mechanisms (filter through the data)
  • The more detailed the graph is the mode elements/nodes it has
  • Objects that look alike will be identified as a part of a group (ex. Boxing bars help readers identify groups)
  • Volume, curvature, shading, and color allow more generic judgments
  • Metrics numerical filters
  • Groups text based groups, such as type of employee, lists of items, etc.
  • Time time based filters, such as months, quarters
  • Gradients are ok for sequential rates
  • Rarely use 3D
  • Color has meaning
  • Sequential when you are ordering values from low to high.
  • Divergent when the values are ordered and there is a critical mid-point (e.g. an average or zero).
  • Categorical when data falls into distinct groups (e.g. countries) and therefore requires contrast between adjacent color