Just as John Peters argues that the meaning of “information” has changed over the centuries, our notion of data too has changed. What once meant “that which is given” now has associations with surveillance and dataveillance (e.g. Poster and Lyon) and the decline of narrative (a la Manovich). More recent readings emphasize that databases are articulations of power, with built-in assumptions, silences, and even anxieties.
Your assignment is to push this last point and to study and critique a dataset. It is directly inspired by a similar assignment by Dr. Lauren Klein at Georgia Tech.
- Select a dataset. This might be data you’ve gathered in a lab class, demographic or statistical data about Davidson or Charlotte, social media data, crime statistics, or any other large dataset. Some possibilities include:
- Your Google or Facebook data
- Your Twitter archive
- Census Data
- The Million Song dataset
- One of the datasets from the R datasets package
- One of the datasets from the Gephi sample datasets (all are social network datasets
- A newspaper or journal archive
- Energy, food, and waste datasets from Davidson (I can hook you up with these)
- Any other large dataset (What counts as “large”? That’s a question for you to wrestle with.)
- Analyze that dataset. Your analysis should be about 1,000-1,200 words (double-spaced, 1” margins). Your analysis should the following:
- A description of the dataset and what it contains. Discover who, when, where, how, and why the data was collected. Consider other important contexts for the dataset. Spend no more than 200-300 words describing the dataset.
- A deeper analysis of the dataset that integrates themes and questions we’ve raised this semester about data, including (this list is inspired by Michael Sacasas and is not meant to be comprehensive list, nor does every item need to be addressed):
What does this dataset lead us to notice?
What does this dataset lead us to ignore?
What was required of other people to create this dataset?
What technical or human systems were required to make this dataset?
What possibilities for action does this dataset create? What possibilities does it foreclose?
What assumptions about the world does this dataset make?
How might this dataset change the way I interact with others, or how others interact with me?
Who does this dataset empower?
Does this dataset ask me to think less, or more?
What does this dataset tell me about myself? What does it tell me about others?
What is the mode of presentation of this dataset? Does it matter?
Who is the audience for this data?
Does the data make any implicit claims about the world?
Your essay should be focused, and integrate examples with analysis. The best essays will demonstrate an awareness of the implications—and limitations—of their argument, and it should consider multiple perspectives when appropriate.
Be prepared to discuss your dataset in class on Thursday, February 12. The final essay is due on Moodle by 8pm on Monday, February 16.