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|Supports Objectives(s)||Conflict Mapping, Inform Audiences, Monitoring and Evaluation|
- 1 Description of Tool Class
- 2 Principles of Effective Data Visualization
- 3 Additional Resources
- 4 Tools in the Data Visualization Tool Class
Description of Tool Class
Data Visualization (also called "dataviz") tools help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization services.
While many Data Collection tools have Data Visualization features, the term on this website applies to tools for which data visualization is a primary function. For example, Tableau Public, Infogram, and Google Forms are designed explicitly for data visualization, while tools such as engageSPARK and Crimson Hexagon, while possessing some visualization features, are limited because they can only visualize information that has been collected by that service or possess only a few visualization options.
It should be remembered that many datavis tools are non-digital (paint is used to create murals or street art that conveys some message or information). Some tools like Google Sheets, Tableau Public and Excel create charts and graphs that can be embedded into documents or websites. Some services create Infographic visualizations, long-form collections of visualizations that are supposed to be viewed in an email or on a website. Mapping tools are a subset of Data Visualization.
One of the advantages of Data Visualization is that in some cases it can reduce the need for the audience to be literate. Golda Stragies visualizations try to use visual cues so as to be readable by low-literacy audiences.
Principles of Effective Data Visualization
Two Main Types of Visualization
- Exploratory - using data visualization tools to explore data sets and discover trends and stories
- Explanatory - using data visualization tools to tell a story to others
See blog entry, "exploratory vs explanatory analysis" on StorytellingWithData.com.
Identify your Goal
Assuming you are using visualization for explanatory purposes, decide whether you aim to:
This will help you decide the best type of visualization to use. Infographics are closely related to data visualization and may be the best choice if your primary aim is to persuade or surprise. Visage.co nicely explains the differences between data visualization and infographics.
People use many types of media to tell stories with data. Your choice of medium should depend on how, when, and when you expect your audience to engage with your visualization.
- Print (flat)
- Digital (flat or interactive)
- Video/audio (animated)
- Installation (physical) - see examples on dataphys.org
Edward Tufte's Design Principles
Tufte is a professor and statistician who has written at length about the best ways to display quantitative data. This is a selection of his most useful principles:
Eliminate Chart Junk
Improve Data to Ink Ratio
Incorporate Multivariate Data
Integrate All Visual Elements
- Visualization Tasharuk's Data Visualization page (English, Arabic, Farsi) has guides for data visualization best practices.
Tools in the Data Visualization Tool Class
- Advanced Summary
- Advanced Summary/en
- Google Forms
- Google Forms/ar
- Google Forms/en
- Google Fusion Tables
- Tableau Public