Research Guides: Data Visualization: About Data Visualization

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What is Data Visualization

Data visualization is a way of exploring complex patterns or large quantities of data that cannot be easily perceived by looking at a table of numbers or reading paragraphs of text. The goal of data visualization is to communicate information more clearly, and it does so by employing our innate ability to recognize visual patterns in our environment.

Some data visualizations are exploratory in that they are created before any analysis is done on the data. Looking at a visual representation of our dataset can give us clues about what to focus on during analysis.

Some data visualizations are communicative in that they are created in order to present our analysis findings to an audience. Using visual patterns to represent patterns in data can be an effective way of explaining complex results.

Ultimately, data visualizations can more effectively answer questions, tell stories and put forth arguments than words alone.

Glossary

Data visualization can be a complicated set of processes to learn. A good starting place is to learn a bit of the vocabulary you may see in the various tools and tutorials.

Data visualization
An umbrella term, usually covering both information and scientific visualization. This is a general way of talking about anything that converts data sources into a visual representation (like charts, graphs, maps, sometimes even just tables)
Infographics
A specific sort of genre of visualizations. Infographics have become popular on the web as a way of combining various statistics and visualizations with a narrative and, sometimes, a polemic.
Information Visualization
A broad term, covering most statistical charts and graphs but also other visual/spatial metaphors that can be used to represent data sets that don't have inherent spatial components.
Scientific Visualization
Generally, the visualization of scientific data that have close ties to real-world objects with spatial properties. An example might be visualizations of air flow over the wing of an airplane, or 3D volumes generated from MRI scans. The goal is often to generate an image of something for which we have spatial information and combine that with data that is perhaps less directly accessible, like temperate or pressure data. The different scientific fields often have very specific conventions for doing their own types of visualizations.
Visual Analytics
The practice of using visualizations to analyze data. In some research, visualizations can support more formal statistical tests by allowing researchers to interact with the data points directly without aggregating or summarizing them. Even simple scatter plots, when the variables are chosen carefully, can show outliers, dense regions, bimodalities, etc. In fields where the data themselves are visual (e.g., medical fields), visual analytics may actually be the primary means of analyzing data. The process of analyzing data through visualization is itself studied by researchers in the visual analytics field.