Lab Topic

Collaborative Lab Notes Doc

Instructions

For this lab, you should spend at least 5 days, but ideally one week, doing the following:

  1. Recording data about some aspect of your personal or professional life, along the lines of what Giorgia Lupi and Stefanie Posavec record in Dear Data;
  2. Creating a custom visualization to communicate that data to readers, thinking about the relationship between the data itself and the mode of sharing it through visualization or—following our #DHMakes discussion—data physicalization;
  3. Writing up the process and your visualization/physicalization, explaining the choices made and the ways this process of critical making has helped you think more deeply about both the aspect of your life the data recorded, as well as about data and the rhetoric of visualization themselves. This final writeup will be a little longer than a typical lab report, at 1000-25000 words.

As this is a longer lab assignment with more expected outside of class, you will have 4 weeks to complete it rather than the typical 2.

Prewriting (in class 11/7)

For this prewriting assignment, you must choose what data you will be recording and outline your methods for doing so, in preparation for actually recording the data in a week soon to come.

  1. First, you will need to identify some aspect of your personal or professional life that you believe would be revealing in aggregate. You might record each time you say “thank you” through the week, but what would you hope to learn by doing so? You should choose some regularly recurring aspect of your daily life that you suspect would, if collected, offer new interpretive purchase for understanding yourself, your professional life, or similar. Now, it’s possible that you will collect data that ultimately does not offer such purchase. This is always a possibility when researchers collect data. But you should choose something that might even be telling in its absence of interpretive power: e.g., “I thought recording each time I said ‘thank you’ would reveal something about my own gratitude and outlook toward other people, but instead…”
  2. Second, you will need to decide what specific aspects of your chosen phenemenon you will record, and determine how you will do so. For “thank you’s,” for instance, would you record the precise wording of each one? The words or actions that prompted you to say “thanks?” The responses of the people thanked? Would you seek to characterize your tone, or that of your interlocutors?
  3. Once you decide what you will record, you will need to determine how. Will binary recording (making a mark in a notebook for each instance) be sufficient, or will you require text, or numbers? Will you carry around a notepad or use an app on your phone? How will you remember to record your chosen phenomenon, particularly if it’s very common in your daily life that might pass unnoticed?

During our lab today, we will spend a little time drafting ideas and then we will workshop them in groups. The latter part of the lab will be devoted to brainstorming ideas about what you will make.

Collecting Data

After class, you should identify a time when you can collect the relevant data. You should aim to collect data over at least 5 days, and ideally one week.

Making Your Data Manifest

Once you have recorded your data, you will need to decide how to represent it visually and/or physically. You might do this analog, following the model of Lupi and Posavec, or you might use a digital platform. Either way, however, I strongly discourage you from using out-of-the-box visualizations, such as the graphs in Excel. If you are engaged actively with the questions above, your data will likely be too individual and nuanced for such solutions, and the point of this lab is to pressure those standard data representations. You should be asking questions such as:

  • How can you convey the unique contours of your data in ways that are revealing for you and your readers?
  • Can your visualization/physicalization say something about the data itself—contribute to its argument, following Isabel Meirelles’ dichotomy of visualization types?
  • Can you balance clarity and complexity in your design, using the affordances of visual or physical media to make your data more, rather than less, legible?
  • Does your visualization/physicalization do interpretive as well as aesthetic work?

You should present images of your final visualization/physicalization along with your longer-than-usual lab report.

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