“Data” is often considered to be the domain of scientists and statisticians. But with the proliferation of databases across nearly all aspects of modern life, data has become an everyday concern. Bank accounts, FaceTime records, Snapchat posts, Xbox leaderboards, CatCard purchases, your DNA—at the heart of all them is data. To live today is to breathe and exhale data, wherever you go, online and off. And at the same time data has become a function of daily life, it has also become the subject of—and vehicle for—literary and artistic critiques.
This course explores the role of data and databases in contemporary culture, with an eye toward understanding how data shapes the way we perceive—and misperceive—the world. After historicizing the origins of modern databases in 19th century industrialization and census efforts, we will survey our present-day data landscape, considering data mining, data visualization, and database art. We will encounter nearly evangelical enthusiasm for “Big Data” but also rigorous criticisms of what we might call naïve empiricism. The ethical considerations of data collection and analysis will be at the forefront of our conversation, as will be issues surrounding privacy and surveillance.
Upon completion of DIG 210, students will be able to:
- Develop a timeline of the rise of databases
- Compare the symbolic power of databases in contemporary life with their functional role
- Analyze a data set with one the common digital tools for data analysis and visualization
- Appraise arguments for and against “Big Data” as an interpretive mechanism
- Experiment with the way identities are constructed through data
- Evaluate competing claims about the ethical collection and use of social data
- Dave Eggers, The Circle (Vintage, 2013, ISBN 978-0345807298)
- Various journal articles, book chapters, and online material, available through the library, Moodle, and the class website
The graded work for DIG 210 will take several forms, detailed below: (1) engagement; (2) weekly blogging; (3) a data critique; (4) a quantified self assignment; and (5) a data-based project.
- This class places a high premium on engagement. It is essential that everyone has carefully considered the day’s material, attends class, and participates. Participation may include small in and out-of-class quizzes and writing assignments. I also expect students to bring the day’s readings to class, well-marked up with notes and annotations. Because much of what we learn this semester will come from each other, more than two absences will lower your engagement grade by at least 10 percent. More than four absences will reduce your engagement grade by 50 percent. Participation is worth 20% of the final grade.
- Each student will contribute to the weekly class blog. There will be three roles on the blog, and each week a fifth of the class will rotate through these roles. Students in one group (“Readers”) will post an approximately 250-word critical response to the week’s reading by Monday night at 10pm. Students in another group (“Responders”) will either respond to these posts or to our classroom discussion by Wednesday night at 10pm. A third group (“Observers”) will collect data about our class, ranging from the trivial (e.g. the number of people wearing red one day) to the substantive (e.g. the type of questions asked during a class discussion). The observers will then post this data onto our class blog at the end of every week. Blogging is worth 20% of the final grade.
- The data critique is a close analysis of a large dataset, in which you investigate its sources, how it was collected, issues around privacy or ethics that come into play, the uses to which the data is put, and the ways it represents “truth” or “facts.” The data may be impersonal, such as census statistics, or it may be data that is closer to home, such as the Davidson residential hall energy usage, or even data about your Facebook network. The data critique is worth 20% of your final grade.
- The quantified self assignment will contextualize the quantified self movement against the larger backdrop of data analytics. For this project every student will be issued a fitness tracker; the data from that tracker and the experience of wearing it form the basis of this assignment. The quantified self assignment will be accompanied by a data visualization of your own making and reflective analysis. The quantified self assignment is worth 20% of your final grade.
- The data-based project is not a database; rather, it is an opportunity to reconfigure a set of data into an argument about that data. In other words, your task is to transform an existing data set—through the interface, its visualization, and so on—in a way that highlights some underlying argument you want to make about the data. The project may be speculative, in the form of a mock-up or proof-of-concept. The data project will be accompanied by a 3-4 page analysis of your project. It is due at the end of the exam period, but you may hand it in earlier. The data-based project is worth 20% of your final grade.
I will evaluate the blog posts according to the following 0-3 point scale:
3 – Exceptional. The blog post is focused and coherently integrates examples with explanations or analysis. The post demonstrates awareness of its own limitations or implications, and it considers multiple perspectives when appropriate.
2 – Good. The blog post is reasonably focused, and explanations or analysis are mostly based on examples or other evidence. Fewer connections are made between ideas, and though new insights are offered, they are not fully developed. The post reflects moderate engagement with the topic.
1 – Insufficient. The blog post is mostly description or summary, without consideration of alternative perspectives, and few connections are made between ideas. The entry reflects passing engagement with the topic.
0 – No Credit. The blog post is missing or late, or simply rehashes previous comments, and displays no evidence of student engagement with the topic.
Every other assignment will be given a letter grade that has a percentage equivalent:
A = 98% /A- = 92%
B+ = 88% / B = 85% / B- = 82%
C+ = 78% / C = 75% / C- = 72%
D+ = 68% / D = 65% /F = below 60%
I am committed to the principle of inclusive learning. This means that our classroom, our virtual spaces, our practices, and our interactions be as inclusive as possible. Mutual respect, civility, and the ability to listen and observe others carefully are crucial to inclusive learning.
Any student with particular needs should contact Nance Longworth (x2129), the Academic Access and Disability Resources Coordinator, at the start of the semester. The Dean of Students’ office will forward any necessary information to me. Then you and I can work out the details of any accommodations needed for this course.
Students at Davidson College abide by an Honor Code. The principle of academic integrity is taken very seriously and violations are treated gravely. What does academic integrity mean in this course? Essentially this: when you are responsible for a task, you will perform that task. When you rely on someone else’s work in an aspect of the performance of that task, you will give full credit in the proper, accepted form.
Another aspect of academic integrity is the free play of ideas. Vigorous discussion and debate are encouraged in this course, with the firm expectation that all aspects of the class will be conducted with civility and respect for differing ideas, perspectives, and traditions. When in doubt (of any kind) please ask for guidance and clarification.
While this course embraces the digital world it also recognizes that digital tools and environments complicate personal interactions. Studies have shown that students who use laptops in class often receive lower grades than those who don’t. Even more worrisome are studies that show laptop users distract students around them. I permit laptops and tablets in class, but only when used for classroom activities, such as note-taking or class readings. Occasionally I may ask students to turn off all digital devices.
Text messaging or other cell phone use is unacceptable. Any student whose phone rings during class or who texts in class will be responsible for kicking off the next class day’s discussion.
Late arrivals or early departures from class are disruptive and should be avoided.