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Introduction to Data Visualization

Rebecca Bartlett, Heather MacDonald, Scott Turner

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Overview

Introduction to data visualization theory
Examples of data visualizations
Guide to data visualization

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Data Visualization Theory

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What is Data Visualization?

Data (or information) visualization is used to interpret and gain insight into large amounts of data. This is achieved through visual representations, often interactive, of raw data.

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Data Visualization:

Enhances learning
Enhances understanding
Enhances reasoning
Helps in decision making

Data visualization acts as a link between the raw data and our engagement with it.

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Data Visualization…

Can then prompt a user to

Draw inferences

Anticipate potential trajectories and outcomes

Ask new questions of the data that wouldn’t have otherwise been considered

Can lead a user to

Detect patterns

Detect trends

Detect correlations in data

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…some visualizations allow the user to filter out undesirable properties in the dataset. This produces a refined list of results to better help with decision making or understanding (think facets on a database).

So let’s apply these ideas to an example:

The Middle East: Key Players & Notable Relationships

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The Data Visualization Catalogue

Provides an excellent introduction to different types of visualizations
Explore the Search by Function feature to find the best visualizations for a given purpose

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Thinking about Creating a Data Visualization

Determine what you are ultimately trying to communicate
Determine which visualization best achieves your aim in the clearest manner possible

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Further Considerations

What data (or subset of data) is relevant for your aim?
Who is your audience?
How will you encode your data?
How will you structure the visualization?
How will you demonstrate the relationship between data?
Determine the scale of your visualization.
Which elements will the user interact with?
Will a user intuitively understand how the visualization works and what it represents?