Digital Humanities Pedagogy – Amanda Madden (George Mason University)
This workshop will cover how to incorporate digital humanities into your graduate and undergraduate courses. In particular, we will discuss how to teach with the rich digital resources for teaching and research in Renaissance Studies and how to design assignments using tools like StoryMaps, Omeka, TimelineJS, Tropy, and Voyant. The first part of the workshop will include a presentation and demonstration; the second part will include discussion. Participants should come with an assignment they would like to explore or a resource they want to use.
Introduction to Computer Vision for Book and Art History – Giles Bergel (University of Oxford)
This lecture and hands-on workshop provides an introduction to computer vision – the extraction of information from images – for the purposes of book and art history. The lecture will give an overview of the field, with particular reference to collaborative research performed by the Visual Geometry Group (VGG) at Oxford. In the hands-on workshop participants will have the chance to try out tasks including visual search, illustration detection, image classification and comparison on supplied examples of Renaissance art and books. No prior experience of computer vision is required: the workshop can be followed either through web demos or user-installable software.
Spatial Humanities – Randa El Khatib (University of Toronto)
This offering consists of a presentation and a workshop. The presentation will provide an overview of the field of geospatial humanities and the steps involved in creating a map from a text. Participants will learn about key concepts, terminology, and resources they need to get started on their projects. We will also explore what types of research questions can be asked and answered using mapping technologies.
In the workshop portion, participants will practice the basic steps involved in building a geospatial project, including how to extract geodata from a text, how to organize and enrich spatial data, and how to visualize that data on a variety of user-friendly, open-access mapping platforms.
Both sessions are intended for beginners.
Introduction to Text Encoding – Isabella Magni (HathiTrust Research Center and Indiana University) + Paolo Scartoni (Rutgers University)
In this lecture + workshop we will explore basic issues of conceptualizing, planning for, managing and building digital editions and we will provide a hands-on introduction to text encoding. Examples from real-life projects, among which the Petrarchive, will be provided. Through guided hands-on encoding exercises, participants will discover the logic behind text mark-up languages and will learn basic encoding skills. By the end of the workshop, participants will be able to read and understand basic TEI mark-up languages; will have thought through the logic and potentials of encoding literary texts; and will have encoded (at least) one poem or prose.
This is an introductory workshop: no previous knowledge of technical skills nor previous experience in text markup is necessary.
Network Analysis – Jessica Otis (George Mason University)
This workshop offers a basic introduction to the construction and analysis of networks. Participants will be introduced to key concepts in formatting network data, analyzing and interpreting networks structures, and visualizing network graphs. They will also be introduced to popular cross-platform digital humanities tools for the visualization and analysis of networks.
Data Organization and Visualization for Beginners – Angela Dressen (Harvard University / I Tatti) and Catherine Walsh (University of Montevallo)
This session will begin with short presentations on a digital art history project (“Mapping Sculpture”), and show how data for this project were collected and organized. We will then provide a basic introduction to spreadsheets and how to use spreadsheets to organize data. A variety of platforms and file formats, including .xlsx, .csv, and Google Sheets, will be reviewed. During the second portion of the session, we will demonstrate how to clean and enhance your data with Open Refine, and how to visualize data with platforms such Carto, Palladio, Tableau and others. Following these demonstrations, we will facilitate a hands-on session during which participants can explore some of these presented tools (bring your own computer). This session is intended for beginners.
Using Jupyter Notebooks and Pandas to Work with Data – Richard Freedman (Haverford College, USA) and Daniel Russo-Batterham (Melbourne University, Australia)
The Pandas Python library has in recent years emerged as a powerful but also surprisingly friendly way to organize, clean, sort, analyze and visualize all kinds of data. In this session we will introduce RSA members to the possibilities of this toolkit for humanistic research.
There will be two sessions:
- One Hour General Introduction (open to all) Thursday February 24, 2022 @ 3PM EST
- Two Hour Hands-On Workshop (15 participants maximum) Thursday March 3, 2022 @ 3PM EST
What you’ll learn:
- You will learn the basics of Pandas (and thus Python)
- How to create and use a Jupyter Notebook in any browser connected to the internet, and avoid the need for complicated installation of code
- How to import and export data from CSV or Excel documents (and other structured datasets like JSON)
- How to understand data types in your data set (dates, locations, text strings, numbers of various kinds)
- How search, filter, clean, group, and combine data sets in various ways
- How to explore large datasets quickly, and how to create simple visualizations
How you’ll learn:
In the first session (one hour), Daniel and Richard will explain some basic Pandas and Python concepts, and how to use a Jupyter notebook. For demonstrations, we will draw on some common ‘test’ datasets, but also show some of the ways we are using Pandas, Python, and Jupyter Notebooks in the context Citations: The Renaissance Imitation Mass (crimproject.org). Along the way you will see how we can explore, edit, and filter large datasets, and how to produce simple visualizations.
In the second session (two hours) of the session we will help a limited number of participants start up and run their own Notebooks, and work with some sample datasets demonstrated in the first part. We will also invite participants to bring their own datasets (Excel documents or CSV files are the best way to start) to the table. You can import and explore these with the Notebook, and we will work with a few volunteers as we coach you through the steps of doing with your own data some of the things we’ve just explained.
What you’ll need:
No previous experience coding is required. Having a second (or large) monitor will allow you to see some of the examples more clearly, and to both work with a Notebook in one browser window while you review reference documents or see a Zoom screen with another.
We’ll show you how to make use of some Jupyter notebooks hosted at our institutions. But if you have a gmail account, you can also easily work with Google Colab (https://colab.research.google.com/)
Doing some advance work to gather a data set would also be helpful. As noted above, having Excel or CSV files ready would be a good start. We encourage you to be in touch with the presenters in advance so that we think ahead about how we can learn together.