Data Visualization

“Perfection is achieved, not when there is  nothing more to add, but when there is nothing left to take away”

Elegance is dashboard design is a macro example of managing the data to ink ratio for the whole screen combined with great IA. Then highlight the most important pixels. Choose chart types that work in small spaces.

Dashboard UX Definition
A dashboard is a visual display of the most important information (not all information) needed to achieve one or more objectives that has been consolidated to a single screen so it can be monitored at a glance.

A chart tells a data relationship single story.
A dashboard provides an aggregate battlefield overview.

The battlefield requires Situational Awareness
Level 1: Perception of elements in the environment (what’s changing and going on)
Level 2: Comprehension of the current state
Level 3: Projection of future status

HFE Performance Monitoring Process (~24 minutes of DataVis2 Pt1)
1. Update high-level situational awareness
2. Identify and focus on particular items that need attention
• Update awareness of this item in greater detail
• Determine whether action is required
3. If action is required:
• Access additional information to understand side effects
• Access tools to take action on objects (embedded case)
4. Return to monitoring the process

Fundamental Design Considerations
• Update frequency (not real-time design) (daily updates?)
• User expertise (experts could interpret very dense analytics)
• Audience size (one person vs. entire company)
• Tech platform (desktop, browser or mobile)
• Screen size
• Data types (quantitative, non- quantitative)
• IA tends to have 3 styles:
– Hierarchy (frequently used; decomposition of dimensions/measures going down the page)
– Process flow (tells story as you move from one side to another)
– Portal aggregation levels

A dashboard is just a UX style of information presentation.
It is NOT a technology as many vendors would like to claim. Dashboards need their own
UCD process and cycle.

Reminder – Interaction with visual info
• Comparing (over time or to a reference value)
• Sorting
• Filtering
• Highlighting (“brushing” – synchronized color selection in dashboards)
• Re-visualizing (change chart type)
• Re-expressing (change units, e.g. dollars to euros)
• Re-scaling (time, days vs. months)
• Zooming and panning
• Detail on demand (hover over point)
• Drill to detail
• Annotate
• Bookmark
• Aggregating (e.g. sales by product by region by year, pivot)
• Adding measures (raw or summarized, statistics & forecasts)

Bar charts are effective show differences or rank.

Typical Defects in Dashboards
• Exceeding the boundaries of a single screen
• Supplying inadequate context for the data
• Displaying excessive detail or precision
• Expressing measures indirectly
• Choosing inappropriate media of display
• Introducing meaningless variety
• Using poorly designed display media
• Encoding quantitative data inaccurately
• Arranging the data poorly
• Ineffectively highlighting what’s important
• Cluttering the screen with useless decoration
• Misusing or overusing color
• Designing an unappealing visual display

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