Liberal Arts Data Bootcamp – Winter Term 2016

See a retrospective video of this event:

January 19th-22nd, 2016, 1:00-4:00 P.M.
Location: Wilson Media Lab, 220 Davis Family Library
Open to all Middlebury faculty, staff, and students

Photograph of silhouette of woman in front of projected data art project
Photo by Flickr user r2hox, used under Creative Commons Licensing.

Are you new to working with data for digital scholarship? Alicia Peaker and Ryan Clement will be offering a workshop series, January 19-22, that will introduce participants to the basics of working with data as well as some free, web-based tools. The series includes one required course, “Working with Data,” as well as three à la carte courses over the following three days on mapping data, visualizing data, and analyzing textual data. Attend one, or attend all four! All courses will be 3 hours long and will include discussions of background concepts as well as hands-on work. Because these courses will be tailored to the participants’ interests and disciplines, the deadline for signing up is January 1st. Please contact Alicia Peaker or Ryan Clement with any questions.

Prerequisite Course

Working with Data

What is data and how do you work with it? In this course, participants will work in teams to interpret, clean, and understand a dataset provided by the instructors. We will then reflect on this exercise and discuss the process and products of working with data, while learning how to manage and make this practice more efficient. No experience working with data is expected, though some familiarity with MS Excel will be helpful. This course is required to participate in any of the next three session of the Liberal Arts Data Bootcamp.

À la Carte Courses

Visualizing Data

In this session, we’ll cover some of the basic theory of visual communication, including how to choose the best visual representation for your data, and best practices for preparing visualizations for print, the web, or presenting. We’ll discuss traditional representations, including bar, line, and scatterplots, as well as touching on more advanced representations. After a discussion of how visualizations are used (and advanced) in humanistic research, we’ll use freely available web-based tools to create our own visualizations.

Mapping Data

In this session, we’ll work through how to prepare, use, and present spatial data. We’ll start with an overview of spatial literacy topics, including how to select a projection (and why it’s important), working with map layers, and basic cartographic theory. We’ll then explore some library resources for creating maps and obtaining spatial data, and then create our own maps using free, web-based tools.

Analyzing Textual Data

In this session, we’ll work through how to prepare, use, and analyze textual data (e.g. novels, newspapers, journals, plays, survey responses, etc.) to address humanistic research questions. While quantitative approaches may be appropriate for some research questions, this session will primarily focus on text mining as an exploratory practice that leads to or helps refine analysis.

Reserve your spot now for the Liberal Arts Data Bootcamp, co-taught by Alicia Peaker and Ryan Clement.