Fundamentals of Digital Scholarship introduces participants to the core stages of digital scholarship’s research workflow: the acquisition, manipulation, analysis, and presentation of data. This seminar serves as a springboard for faculty, students, and staff who wish to explore the potential of digital scholarship. It will provide a solid foundation from which participants can continue to develop these skills whether on their own or through a series of advanced, subject-specific follow-up seminars.
Register via the Harvard Training Portal.
The seminar is structured as a series of hands-on sessions that provide participants with the opportunity to work with real-world datasets that relate to the humanities and social sciences. These sessions will teach participants how to:
- Create digital datasets by mining online resources or digitizing paper materials,
- Effectively store and organize those datasets
- Prepare the data for analysis
- Use beginner-friendly visualization techniques to explore datasets, and
- Present the results in various formats on multiple platforms.
Feedback from previous seminar participants has been positive. "This was excellent," said one participant. "All the lecture material was engaging, useful, succinct, clear and I liked how every speaker tied their piece into the overall concept." Another said, "I liked the comprehensive and interlinking aspect of the workshops. It gave me a nice sense of a digital project from start to finish. All the presentations were easy to follow [and] engaging." "I now have a much better mental model of what is involved with digital scholarship," said another participant, "and feel ready to embark on my own project or guide others."
This workshop will be delivered via Zoom. Participants are free to join as many sessions as they like, but are encouraged to attend the entire workshop as some sessions build on earlier sessions.
Participants will watch 3 pre-work videos, which will present a condensed version of what is typically day one of the workshop
- Data Structures
- Web Structures & Data Formats
- Getting Data & Data Sources
- 10:00 - 10:25 am: Introduction and recap of videos
- 10:25 - 10:50 am: Cleaning Data in Google Sheets
- 11:00 - 12:00 pm: Visualization for Exploratory Data Analysis
- 12:00 - 1:00pm: Lunch break
- 1:00 - 1:50pm: Hosting and Displaying Results
- 2:00 - 2:50pm: Exploring Digital Scholarship Methods and Projects