Data Selfies – An Introduction to Cleaning and Visualizing Data
|Institution:||University of Arkansas—Fayetteville|
|Category:||Data Visualization, Information Design, Interaction Design|
|Filed Under:||Brainstorming, Data Visualization, Digital, Experimental, Four-year Program, Information Architecture, Storytelling, Technology, Visualization|
- Select a period of time in your life and a series of behaviors/events/happenings (or potential data sets).
- Enrich your data within Google Sheets, taking variables, tables, and conditional formatting into consideration. What are your insights? What is the story you will tell?
- "Digitize" your data using Tableau, RawGraphs, Carto, Excel, or "from scratch". Iterate and refine toward one final dynamic data visualization.
- Situate your data visualization within static space in the form of a poster that invites an audience to engage.
- Use motion design tools demo-ed in class to iterate on the poster, exploring narrative through speculative + digital interactions
Discover avenues and resources to collect and clean personal information into a usable data set. Using the resulting data set and knowledge of narrative, design compelling visualizations that encourage a viewer to draw conclusions.
- One "Cleaned" data set in Google Sheet or Excel
- One large format (28"x44") poster (printed & pdf)
- One .mp4 video of a speculative digital interaction journey
Data Points: Visualizations that mean something by Nathan Yau
A collaborative taxonomy completed by students of "The Visual Language of Data Viz"
Students were asked to research and report on a type of data visualization and report in a collaborative document that was used as a visual resource for both classes doing the project
Chart Suggestions - A Thought Starter
Students were very receptive toward this project, excited at the prospect of mastering new tools and their ability to do this kind of work. I was impressed with the level of detail, dedication, and curiosity students had regarding their personal data. They were creative and ambitious with their collection, cleaning, and visualization. I observed clear learning, as students went on to do more data visualization in other classes to great success.
We spent a good deal of time discussion data visualization and infographics. Group discussion surrounding the differences, capabilities, and various uses was helpful for students during their process.
Some students became frustrated with visualization software such as Tableau and Raw Graphs. Those that opted to design their data viz from scratch seemed more successful but also more overwhelmed.
Next time I do this project, I would like to connect it more deeply to data bias and interpretation. Students struggled to find concrete correlations and takeaways from some of the more complicated data sets.
Additionally- I think the interactive data portion of this project may have been too advanced or convoluted for this particular group.