Advancements in computing and computational data mining have resulted in the ability to garner much larger and diverse statistics than were previously available. This massive influx of data availability quickly becomes unwieldy without the use of visual shorthand. Daniel Carr has developed numerous techniques and formations for better capturing and representing quantitative data in a visual medium. By using data visualization techniques, analysts and researchers, such as those for the National Institutes of Health, are able to gather context and formulate theorems more efficiently. For instance, by examining a map of a region effected by an outbreak of E. Coli illness superimposed with distribution routes of produce, environmental factors, age demographics, etc., epidemiologists are better equipped to zero in on the source of infection.
In his 25 year history at George Mason University, Carr has taught a variety of classes in statistics graphic design and data exploration. He has served as dissertation director for more that 10 graduated PhD students, and co-authored the book, “Visualizing Data with Micromaps,” with Linda Pickle in 2010.