Data visualization refers to representing data in a visual context, like a chart or a map, to help people understand the significance of that data. Visualization is a frequent final output of research. Putting some time and strategic thought into data visualization at the beginning of a research project can help you create more effective visualization. (For more on data visualization, see the "Data Visualization" section in DS Methodologies Overview.)
Data visualization is usually one of three types:
Scientific visualization, meaning the representation of scientific phenomena that tend to be tied to real-world objects with spatial properties e.g., modeling airflow over an airplane.
Information visualization under which falls most statistical charts and graphs and also includes other visual and spatial representations.
Infographic, meaning a specific sort of visualization that combines information visualization with narrative.
In the video below, David McCandless talks about how we can use visualizations to make data more meaningful. He explains who he turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections.