All meetings will be held in the Wilson Media Lab 220 LIB.
Are you new to working with data for digital scholarship? In this DLA sponsored workshop series, we will teach you some of the basics of working with data as well as some free (and mainly web-based) tools you can use to visualize data, map data, and analyze textual data. The series will include one required course on the first day, as well as three à la carte course over the following three days. Attend one, or attend all three! All courses will be 3 hours long and will include discussions of background concepts as well as hands-on work. Please contact Alicia Peaker or Ryan Clement with any questions.
| Title | Date | |
|---|---|---|
| Liberal Arts Data Bootcamp – Working with Data @1pm until 4pm | January 19, 2016 | View & sign-up » |
| Liberal Arts Data Bootcamp – Visualizing Data @1pm until 4pm | January 20, 2016 | View & sign-up » |
| Liberal Arts Data Bootcamp – Mapping Data @1pm until 4pm | January 21, 2016 | View & sign-up » |
| Liberal Arts Data Bootcamp – Analyzing Textual Data @1pm until 4pm | January 22, 2016 | View & sign-up » |
Tuesday
- Title: Working with Data
- Instructor: Ryan Clement
Description: 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 instructor. 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 the next three session of the Liberal Arts Data Bootcamp. If you are already familiar with working with data and would like to participate in later sessions, please contact Ryan Clement.
Wednesday
- Title: Visualizing Data
- Instructors: Ryan Clement & Alicia Peaker
- Prerequisite: Working with Data
Description: 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.
Thursday
- Title: Mapping Data
- Instructors: Ryan Clement & Alicia Peaker
- Prerequisite: Working with Data
Description: 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.
Friday
- Title: Analyzing Textual Data
- Instructor: Alicia Peaker
- Prerequisite: Working with Data
Description: 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.
