Weekly Data Viz #10

Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. This week we did it on a Wednesday. Eurry writes:

A few people have asked me about my process for building visualizations. It’s kind of flattering! Well, it’s a simple answer and not far from what those of us in the class already do — exploratory data analysis. It’s the process of trying to find quirks, trends, surprises, relationships, and outliers in the data. Most of the time, it is REALLY difficult to find the proverbial needle in the haystack. Other times it’s hard to tell what has enough substance to end up as a visualization? One common theme is that the overall process truly depends on the expected audience for the visualization. Who is the audience? Are they domain experts? Is it business folk? Is it everybody?

If the visualization is meant to be explanatory, then maybe more of a descriptive visualization is needed than a narrative one. That said, this shouldn’t stop you from teasing out portions of the data and arriving at a compelling datapoint or relationship. Above all, it’s really about the audience… but it’s also subjective. It’s what you think is important. But above all, remember clarity and data integrity.

This week’s visualization is a good example of the emphasis on audience. In this interactive website about the interesting story of our “real” consumption of water, the narrative flows from aggregate statistics plucked from the data. It’s a bunch of descriptive statistics used to form a familiar but surprising story. And I love the annotation layer. A little bit of description about the graph goes a long way! Sure, the fact of your description may be completely obvious, but (especially!) when it comes to narrative visualizations, it is a crucial step in building up to the climax of your thesis. Don’t underestimate pointing out the obvious.


Lastly, here is a nifty summary of visualization methods to inspire you:


It is a fantastic summary of the “little” elements of visualization that may seem invisible to you at first, but are crucial to curating an understanding from your audience.



One comment

  1. That’s lovely example =)

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