Introduction to Data Visualization
- 1) Simplify users’ lives through modern, intuitive interfaces.
- 2) Empower users through intelligent, personalized displays.
- The following recommendations will help you align with these principles:
- Chart Types
- Color Usage
- Controls & Layout
Our approach to data visualization is in keeping with the broader guiding principles of Spark, especially:
1) Simplify users’ lives through modern, intuitive interfaces.
When illustrating complex data relationships, the goal is to provide clarity. We have adopted a display that minimizes clutter, promotes focus and strives to achieve an “efficient communication of complex quantitative data.” (Edward Tufte)
2) Empower users through intelligent, personalized displays.
In addition to providing clarity, successful data visualization informs users and provides insights necessary to make decisions.
The following recommendations will help you align with these principles:
Keep it Simple
Strive for an immediate understanding of what the data represents.
Eliminate Redundancy
Do not include multiple visual affordances for the same information.
Focus on the Data
Keep controls and additional content to a minimum. Use progressive display to provide access to detailed content.
Give Users Control
Include effective and intuitive controls for allowing users to configure the data.
Chart Types
Depending on the application there is a variety of data visualizations to choose from, click on one to explore:
Color Usage
Color should be used in a manner that is consistent with the Spark Color Palette, click here to see all Data Visualization Color Palettes.
Controls & Layout
The following page illustrates a common layout for data visualizations and the location for controls and information that appears alongside most charts and graphs.
Layout & Information Hierarchy
The sequencing of elements may vary based on the information hierarchy of your page. For example, the KPI Bar should appear at the top of the page if it does not change based on the tagging control above it.
Some additional variations include:
(Click image to open full resolution)
Each of the above layouts are available in the Data Visualization PSD file.