Assignment 3: Data Visualization (Data Storytelling)
The goal of this assignment is to communicate complex principles with simple and graphic visualizations. Students will explore data management software such as Microsoft Excel and Tableau, as well as Adobe Illustrator and AfterEffects. Software training will also be supplemented with lectures and workshops that address the design principles behind graphical excellence and data communication. Here are some additional resources that may be useful:
Note: you will need to continue to develop your testing apparatus as you begin to collect (and respond to) your data. Continue to do document improvements and iterations and post them on your website. In order to effectively collect data from multiple experiments, you will need to establish a clear methodology. Do not wait to visualize your data until the end of the project – you will need to visualize as you go to ensure that your methods are effective.
Part 1: Data Management (25%)
Maintain a spreadsheet that is organized and can be shared with project collaborators. This is one document that contains all of your project data in an organized fashion. Submit MS Excel spreadsheet (or whatever format you are working in).
Part 2: Data Storytelling (50%)
Data can be complex and unruly, so data storytelling is an impactful communication tool used to craft a compelling narrative of your own. It can be used to put data insights into context and inspire action from your audience. What data did you observe from your device? How is this useful (or not useful) to telling your story? Does it support your hypothesis? Why or why not?
You may need several visualizations to tell the story of the data. Use your best judgement to determine how many visualizations to include in your final paper. Effective visualizations will focus on creating both clear and compelling visual iterations that reinforce the findings. Please consider:
Your static visualizations should also be supported by some form of animation to be used during your final presentation.
Part 3: In-class pinup (25%)
Tuesday, April 19th. (please come with printed documents, animation can be shown on screen).
Due: Tuesday, April 26th 2:30 PM (upload to website – ‘results’ page)
- Tufte, Edward. The Visual Display of Quantitative Data (2001).
- Tufte, Edward. Envisioning Information (1990).
- Mereilles, Isabelle. Design for Information (2013).
- Yau, Nathan. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics (2011).
Note: you will need to continue to develop your testing apparatus as you begin to collect (and respond to) your data. Continue to do document improvements and iterations and post them on your website. In order to effectively collect data from multiple experiments, you will need to establish a clear methodology. Do not wait to visualize your data until the end of the project – you will need to visualize as you go to ensure that your methods are effective.
Part 1: Data Management (25%)
Maintain a spreadsheet that is organized and can be shared with project collaborators. This is one document that contains all of your project data in an organized fashion. Submit MS Excel spreadsheet (or whatever format you are working in).
Part 2: Data Storytelling (50%)
Data can be complex and unruly, so data storytelling is an impactful communication tool used to craft a compelling narrative of your own. It can be used to put data insights into context and inspire action from your audience. What data did you observe from your device? How is this useful (or not useful) to telling your story? Does it support your hypothesis? Why or why not?
You may need several visualizations to tell the story of the data. Use your best judgement to determine how many visualizations to include in your final paper. Effective visualizations will focus on creating both clear and compelling visual iterations that reinforce the findings. Please consider:
- Movement beyond the surface of the data to question meaning, assumptions and motivations
- An obvious evolution of the concept through continued, aggregated and evaluated research (you will not get it right on your first try. Prove that you learned from the data)
- Effective visualizations should be supported by written components of the research and findings (this will fit directly into your paper)
- An exploration of visual language that is varied, relevant and context sensitive
- An attention to detail and craft which support the research and analysis and show iteration and refinement.
Your static visualizations should also be supported by some form of animation to be used during your final presentation.
Part 3: In-class pinup (25%)
Tuesday, April 19th. (please come with printed documents, animation can be shown on screen).
Due: Tuesday, April 26th 2:30 PM (upload to website – ‘results’ page)