The Humanities Intensive Teaching and Learning (HILT) Institute will be held June 4-8, 2018 on the campus of the University of Pennsylvania in Philadelphia, Pennsylvania.
Registration for HILT courses, our special optional events on Friday, June 9th, and housing will begin on November 20th. Confirmed special events will include an HathiTrust Research Center Workshop as well as excursions to Philadelphia cultural heritage institutions and nightly dine-arounds.
We've got an exciting slate of classes taught by incredible instructors. Courses for HILT 2018 include:
Advocacy by Design
Led by Purdom Lindblad and Jeremy Boggs
This course helps participants consider how their own priorities and values shape the research and design of digital work. For us, a digital humanities that practices critical engagement means centering our priorities and values to make all aspects of our work—research content, project design and development, and community/user interaction—advocate for the people and materials represented within and affected by our work.
Through topics such as feminist design, metadata and information design, and accessibility, participants will gain a set of approaches and methods that they can apply in their own work. Instructors will survey participants before the course to identify tools, methods, and projects of interest. Based on the survey responses, we will learn how to:
- evaluate, use, modify, and critique identified tools and methods and projects;
- begin developing research and development plans for projects that articulate their own priorities for critical engagement;
- practice scoping and prototyping their own projects.
As we work toward these outcomes, we will survey a range of existing critical and applied work related to advocacy, social justice, and Digital Humanities. Course activities will include both reading/discussion and practice-based workshop activities. We place a particular importance on praxis and tacit knowledge, so we will investigate topics through making and critiquing prototypes.
Collections as Data
Led by Thomas Padilla and Mia Ridge
A growing amount of interest has been dedicated to an emerging orientation to collections referred to as “collections as data”(ex. 1, ex. 2, ex. 3). Generally speaking, work in this space seeks to explore what might be possible if cultural heritage organizations began to think about, prepare, describe, and provision access to digital collections in ways that promote their amenability to computational use. During this course librarians, archivists, museum professionals and allied collection stewards will explore how to approach development of collections as data. The course will consider lessons learnt from earlier work on open cultural data, image releases and APIs. Possible user communities served by this work include but are not limited to Digital Humanities, Data Driven Journalism, and Digital Social Science.
Concretely, participants will (1) be exposed to case studies of established and emergent collections-as data work from a variety of institutional contexts (libraries, archives, museums) (2) consider differences and commonalities across a range of user communities (Humanities, Social Science, STEM, and more) (3) build on lessons learned derived from existing real world implementations of collections as data (4) discuss the principles and ethical dimensions of collections as data work.
Connecting Digital Humanities to Public Audiences
Led by Modupe Labode and Elee Wood
Connecting publics to the digital humanities requires skill, persistence, and intentionality at all phases of a project. This course is designed to provide an introduction to public-centered strategies, practices, and questions for development of public projects. Explored through the lens of museum studies and public history, this course will work with participants to identify audiences, develop inclusive practices, and craft community-based interpretations to consider how these strategies can be used to shape and implement digital humanities exhibits and programs. As a class we will explore questions such as: What does shared authority look like when doing digital humanities? How do you know who your audience is and what they may want? How is a digital exhibition or representation similar and different from an in-person exhibition or representation? How does a project know if it is successful? How do you respond to challenges in working with the public? The class will touch on strategies for exhibit development and critique and hands-on planning utilizing case studies of both digital and physical experiences. This course is designed for those at all levels of digital humanities: from novices, to skilled practitioners, to those who work in museums and cultural institutions that sponsor digital projects. Students are encouraged to bring project ideas and conundrums to the course.
***Connecting Digital Humanities to Public Audiences is sponsored by the National Council on Public History.
Digital Methods for Interdisciplinary Cultural Studies
Led by Brandon Locke and Lauren Tilton
How can we transform cultural artifacts, including texts, images, film, and objects into data in productive ways? How do we create, clean, organize, and analyze cultural data without losing its context and meaning? How do emerging digital methods challenge, augment, or complicate cultural studies as they are currently practiced in different disciplines? How do we select, develop, and/or communicate our “digital methods” of cultural data to one another? What counts as “productive” data in cultural studies? How do we understand digital cultural studies as an interdisciplinary endeavor?
In Digital Methods for Interdisciplinary Cultural Studies, we will begin by considering how traditional concepts of “primary”, “secondary”, and “tertiary” sources can be studied individually or at scale. We will explore approaches to (1) finding, evaluating, and acquiring (2) cleaning and preparing (3) exploring (4) analyzing (5) visualizing, and (6) communicating and sharing data. We will discuss the iterative nature of data preparation, the challenges of working with data of different scales or types (e.g. “dense”, “complex”, “big”, “mixed”, “problematic” etc.), as well as how decisions about methodology, tool selection, and data representation can shift according to one’s goals. Emphasis will also be placed on how to manage an emerging digital research project in such a way that helps to ensure that your project remains accessible, that the process is well documented, and that the data is/are reusable.
This course is intended to be an introductory course, and no prior technical experience or knowledge is expected. Readings will be provided to help assist participants in core concepts, methods, and decision making. Participants are welcomed to bring their own data with them that they might want to discuss during class.
Digital Surrogates: Representation, Engagement, and Meaning
Led by Dot Porter
This course asks participants to learn about the process of creating digital surrogates with attention to issues of representation, engagement, and meaning. Beginning with the question “What does it mean to digitize an object?”, participants will be asked to consider the responsibilities of a digitization project as it is related to paid and unpaid labor, the ethics of working with digital material, and how decisions about technical standards and platforms can facilitate or limit future use of digitized materials. Framed via critical readings on feminist labor and digital humanities work, participants will be asked to consider their learning within their own individual and institutional values and support systems. Participants in the course will tour the University of Pennsylvania’s SCETI digitization lab, and will have opportunities for experimentation with various analog materials including manuscripts, printed materials, archival holdings, and material objects. Additionally, the course will include experts from UPenn working on the digitization pipeline including photographers, cataloguers, infrastructure specialists, and front-end developers. Topics covered during the course will also include the International Image Interoperability Framework (IIIF), Linked Open Data (LOD), and how digitization frameworks must respond to material differences in the original artifacts.
Help! I’m a Humanist---Humanities Programming with Python
Led by Brandon Walsh and Ethan Reed
This course introduces participants to humanities programming through the use of Python for data acquisition, cleaning, and analysis. The course assumes no prior technical knowledge and will focus on accomplishing basic research tasks. Students should walk away feeling equipped to tackle a variety of typical problems that arise for digital humanists.
We will discuss programming and debugging concepts through the design, implementation, and presentation of small projects working with humanities data. Primary technologies and topics covered in this course will include the command line, Git, GitHub, and Python; working with data sources such as API’s, CSV files, and data scraped from the web; and basic text analysis. Over the course of the week, we will work with data from DPLA and Project Gutenberg. If the words above mean nothing to you, don’t panic—this course is for you. If you intend to bring your own laptop, you will need to have administrative rights in order to install software.
Spaces and Stories in the Black Public Humanities
Led by Jim Casey and Sarah Patterson
In this course, we will discuss the projects, questions, and theories circulating in the growing community of Black Digital Humanities. These ideas include conversations around race, space, and the politics of representing collective and partial histories as data. We will focus on marginalized collections in libraries/archives and building historical knowledge with the communities where those histories live today. This is a course for people who have begun to create digital projects in Black studies, broadly considered. If you have begun to gather and organize information about an archive, collection, or history–but aren’t sure where to go next–this is the course for you.
The course will pair theoretical inquiry with practical, skill-building sessions through attention to the craft of digital narratives for diverse learning communities. These sessions will intersect with a number of critical conversations. How do datasets make arguments? How can we collaborate with archivists, librarians, and information professionals to unpack power, authority, and violence in humanities data? How can these sessions draw on the rich traditions of oral and written Black storytelling? What role does the complexity of our data and instruments play in advancing these projects beyond academic spaces? What, really, are we representing in digital studies of historical and present-day Black collectives?
During the skill-building sessions, we will experiment with maps, graphs, and stories. Using the Colored Conventions Project and trends in data-centric projects as examples, participants will grapple with different methods towards recovering and representing Black publics. We will become acquainted with data management and analysis through mapping and graphing tools, including Google My Maps, StoryMap, Social Explorer, and Gephi–among others that may present particular interest to course members. The course seeks to highlight the intersections of project management, digital pedagogy and public-facing community engagement. By the end of the week, participants will have a roadmap for working with data, tools, and more both in the classroom and beyond the walls of our institutions.
Open to all levels of interest and background, course topics will include:
- Identifying and analyzing marginalized histories through texts, metadata, maps and network graphs.
- Understanding the relationship between social justice theories and DH practice
- Visualizing Black publics with open-source and accessible tools.
- Developing data and curricula for diverse coalitions of teaching and learning.
- Course readings made available through a shared Google folder in the weeks before HILT begins.
- Participants are welcome and encouraged to bring their own datasets to use during the course.
Led by Katie Rawson and Scott Enderle
This class will examine methods and practices for text analysis. Freely available tools and excellent tutorials have made it easier to apply computational text analysis techniques; however, researchers may still find themselves struggling with how to build their corpus, decide upon a method, and interpret results. We will survey the how and why of variety of commonly used methods (e.g. word distribution, topic modeling, natural language processing) as well as how develop and manage a collection of texts.
Students who take this course will be able to:
- Find and prepare texts for analysis.
- Store, access, and document their text objects and data.
- Discuss their corpus-building decisions and textual data in ways that are methodologically and disciplinarily sound.
- Identify appropriate text analysis methods for a given question.
- Engage in text analysis methods that use word frequency, word location, and natural language processing.
- Articulate statistical, computational, and linguistic principles — and how they intersect with humanistic approaches to texts — for a few text analysis methods.
We will use a mixture of free off-the-shelf tools and scripts in R and Python (you don’t need to know R or Python to take the class). We will primarily work together from shared data sets the instructors will provide. This course will be appropriate for people at all levels of technical expertise. Students should have administrative rights to load software on their laptop.