Data Communication Principles#
When first learning how to programatically generate data visualizations, it’s easy to be overwhelmed by syntax nuances. Let’s take a step back and think through why we want or need to visualize data.
A quote from NYU engineering faculty Enrico Bertini, whose reserach looks at visual representations of information:
"Visualization projects with high visibility focus on two main purposes: inspiration and explanation. Visualization can however be used (and is actually used) to increase understanding of complex problems through data analysis. These project are less visible but by no means less important...The main goal here is to extract information out of data with the purpose of answering questions and advancing understanding of some phenomenon of interest."
Citation: Enrico Bertini, From Data Visualization to Interactive Data Analysis Medium (28 November 2017).
We can think of data visualization as a means or tool that enables us to do things like…
Analyze an unmanageably large body of primary source materials
Bring together a range of data sets that require computation tools to connect, integrate, or synthesize disparate elements
This page is not designed to be an exhaustive resource on how to approach data visualization as an act of communication. What it does attempt to do is highlight resources and approaches that cover some preliminary condsiderations.