Data visualization is the graphical representation of data, which researchers use to identify patterns, trends, outliers, etc., and for creating visual evidence to support a scholarly claim. The range of visualization chart types vary considerably, e.g., scatterplot, bar chart, and line graph. The kind you will see in the examples here are timeline, maptree, and network. GIS, a form of data visualization that uses geospatial data, will be discussed in the mapping section. (To learn more about data and data visualization, see Introduction to Data.)
Network visualization illustrates connections and relationships between different entities. As to be expected, the intricacy of the networks will impact the complexity of the visualization.
This relatively simple network visualization illustrates the relationships between characters in the film, Lord of the Rings: The Fellowship of the Ring.
Visit to interact with this visualization.
"Six Degrees of Francis Bacon," a more complex network visualization of early modern social networks, is a collaborative project to which multiple scholars and students from around the world have contributed.
Visit to interact with this visualization.
This treemap visualization, which shows exports around the world, is from the Harvard Growth Lab's The Atlas of Economic Complexity and was created using a platform designed by the Lab.
Timelines are a temporal form of data visualization and, depending on the tool, allow for varying degrees of detail and complexity.
This basic timeline of Mary Shelly's life was created with TimelineJS, a simple tool that allows for a single linear visualization.
Visit to interact with this timeline.
"Conflicts of the World," a more complex timeline than the one above, was created with Tableau Public, a popular tool used for creating multiple types of data visualization.
Visit to interact with this timeline.
There are many basic visualization types. Which one you use depends upon the kind of data you are displaying, how you want people to engage with it, and the kind of story you are trying to tell.
Some of the most common types of data visualization chart and graph formats include:
Bar charts are one of the most common data visualizations. You can use them to quickly compare data across categories, highlight differences, show trends and outliers, and reveal historical highs and lows at a glance. Bar charts are especially effective when you have data that can be split into multiple categories.
The line chart, or line graph, connects several distinct data points, presenting them as one continuous evolution. Use line charts to view trends in data, usually over time (like stock price changes over five years or website page views for the month). The result is a simple, straightforward way to visualize changes in one value relative to another.
Pie charts are powerful for adding detail to other visualizations. Alone, a pie chart doesn’t give the viewer a way to quickly and accurately compare information. Since the viewer has to create context on their own, key points from your data are missed. Instead of making a pie chart the focus of your dashboard, try using them to drill down on other visualizations.
Scatter plots are an effective way to investigate the relationship between different variables, showing if one variable is a good predictor of another, or if they tend to change independently. A scatter plot presents lots of distinct data points on a single chart. The chart can then be enhanced with analytics like cluster analysis or trend lines.
