Dashboard design patterns

Benjamin Bach, Euan Freeman, Alfie Abdul-Rahman, Cagatay Turkay, Saiful Khan, Yulei Fan, Min Chen

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This paper introduces design patterns for dashboards to inform dashboard design processes. Despite a growing number of public examples, case studies, and general guidelines there is surprisingly little design guidance for dashboards. Such guidance is necessary to inspire designs and discuss tradeoffs in, e.g., screenspace, interaction, or information shown. Based on a systematic review of 144 dashboards, we report on eight groups of design patterns that provide common solutions in dashboard design. We discuss combinations of these patterns in “dashboard genres” such as narrative, analytical, or embedded dashboard. We ran a 2-week dashboard design workshop with 23 participants of varying expertise working on their own data and dashboards. We discuss the application of patterns for the dashboard design processes, as well as general design tradeoffs and common challenges. Our work complements previous surveys and aims to support dashboard designers and researchers in co-creation, structured design decisions, as well as future user evaluations about dashboard design guidelines.
Detailed pattern descriptions and workshop material can be found online: https://dashboarddesignpatterns.github.io
Original languageEnglish
Pages (from-to)342-352
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Volume29
Issue number1
Early online date26 Sept 2022
DOIs
Publication statusPublished - 1 Jan 2023
EventIEEE VIS 2022 - Oklahoma City, United States
Duration: 16 Oct 202221 Oct 2022
https://www.ieeevis.org/year/2022/welcome

Keywords / Materials (for Non-textual outputs)

  • Dashboards
  • Design Patterns
  • Data Visualization
  • Storytelling
  • Visual Analytics
  • Qualitative Evaluation
  • Education

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