Michael Freeman

Michael Freeman, MPH, is a lecturer at the University of Washington Information School, where he teaches courses on data visualization and Web development. With a background in public health, he works alongside research teams to design and build interactive data visualizations to explore and communicate complex relationships in large data sets. His freelance work ranges from Web design to software consulting, and examples of his projects can be seen here.

Telling your data’s story

How storytelling can enhance the effectiveness of your visualizations.

Editor’s note: this post is part of our investigation into Big Data Design and Social Science. Michael Freeman covers the use of storytelling frameworks in visualizations in his new tutorial video “Using Storytelling to Effectively Communicate Data.”

Visualizing complex relationships in big data often requires involved graphical displays that can be intimidating to users. As the volume and complexity of data collection and storage scale exponentially, creating clear, communicative, and approachable visual representations of that data is an increasing challenge. As a data visualization specialist, I frightened one of my first sets of collaborators when I suggested using this display:

Data Visualization

What I had failed to communicate was that we would use a story structure to introduce audiences to the complex layout (you can see how I did it here).

This image captures three emerging limitations in big data visualization:

  1. Unclear visual encodings: People don’t know what each visual symbol represents
  2. Too much data: The volume of information displayed is overwhelming
  3. Too many variables: Simultaneous encodings of color, position, size, etc. precludes fully understanding each dimension

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