The Humanities Intensive Learning & Teaching Institute is delighted to announce that HILT2016 registration is now open. HILT will be held June 13-16, 2016 with special events on June 17th at Indiana University-Purdue University Indianapolis. HILT is a partnership of IUPUI, IUPUI Libraries, the Maryland Institute for Technology in the Humanities, and MATRIX: Center for Digital Humanities and Social Sciences.
Courses for 2016 include:
Analyzing and Presenting Spatial Data taught by David McClure, Stanford University
This course will introduce students to a range of techniques for analyzing and presenting spatial data in the humanities. We’ll start with a survey of popular GUI-based tools (Neatline, Google Fusion Tables, CartoDB, QGIS, etc), exploring both their capabilities and their limitations. Motivated by the gaps in existing software, the last part of the course will consist of a basic introduction to web map programming in the browser, making use of popular open-source libraries like Leaflet, d3, and Turf.js. Along the way, we’ll touch on the basic concepts needed to get up and running with front-end software development – HTML, CSS, Javascript, and more. This course is designed for enthusiastic beginners who are looking to learn about new tools and and get started with the basic skills needed to create custom GIS applications. No previous programming experience is required.
Building and Sustaining a Digital Humanities Center taught by Julia Flanders, Northeastern University
Digital humanities centers are complex, situated ecosystems that operate within many different kinds of constraints. Starting one is difficult; running one is harder; keeping one going for the long term is hardest of all. This class will look at a range of different types of centers, considering a variety of institutional locations, staffing models, funding approaches, and research agendas. Using real-world cases drawn from the international digital humanities context and from class participants, we’ll investigate a series of practical challenges including communication mechanisms, data management planning, fundraising and fiscal strategies, engaging with students, and space planning. The course will give participants an opportunity to develop concrete plans for their own center (real or hypothetical), as well as a broader familiarity with existing models. Participants should be prepared to think through the practical and intellectual challenges of establishing and maintaining a digital humanities or digital scholarship center. Familiarity with the general landscape of digital humanities will be assumed and will be important for participation.
Database Design for Visualization and Analysis taught by Nicole Coleman, Stanford University
Network graphs, charts, and maps are becoming essential and powerful tools for humanities scholars asking new questions about historical data. Visualization of digitized archives and source materials can reveal patterns previously unnoticed and provide a rich context for research questions. The intellectual work in information visualization begins before we see anything; it begins with the design of the underlying data model. In this course we will work with data from a range of sources and learn how to transform and enrich the data around specific research questions. Then we will engage in an iterative process of visualizing and refining the data. You will learn how to collect, create, manage and manipulate data, how to visualize data in the form of maps, network graphs, and charts, and then produce an interactive data driven document to present the results.
Digital Pedagogy and Networked Learning taught by Lee Skallerup-Bessette, University of Mary Washington and Amanda Licastro, Stevenson University
Many argue digital humanities is about building stuff and sharing stuff, reframing the work we do in the humanities as less consumptive and more curatorial—less solitary and more collaborative. In this workshop, participants will experiment with ways technology can be used to build learning communities within the classroom, while also thinking about how we can connect our students to a much larger global classroom. We’ll start at the level of the syllabus, thinking about how we organize and structure hybrid courses and digital assignments, before delving into specific tools and critical orientations to technology. Participants should expect that the workshop will be hands-on, collaborative, and iterative; we will be using and building, experimenting with the pedagogy we are learning, making our learning environment as we go. The course has no prerequisites. We will work together across skill levels, experimenting with new tools, while adapting and remixing our pedagogies. This isn’t about digital tricks or gimmicks, but a profound re-examination of how we teach.
Exploring Humanities Textual Data with R, taught by Lauren Tilton and Taylor Arnold, Yale University
The application of computational tools to textual data is a growing area of inquiry in the humanities. Much of this work, however, relies on older techniques such as n-grams and bag-of-word models. Recent developments in computational linguists, which have attempted to mimic the complex process by which humans parse and interpret language, have so far failed to gain much wide-spread usage. A primary reason these methods have not enjoyed wider popularity is because many scholars have had limited opportunities to become exposed to them.
This workshop introduces the basic components of modern natural language processing and illustrates how they can be used to extract latent information from a corpus of text. Techniques include tokenization, lemmatization, part of speech tagging, dependency parsing, and co-reference resolution. Students in the course will learn these concepts by way of a tutorial approach: everyone will be expected to follow along on their own machines as we work through increasingly involved examples. The tutorials use the open source statistical programming language ‘R’, however no prior programming experience is assumed. Necessary components of the programming language are introduced throughout the workshop. Our objects of study will be: (1) a collection of short stories, (2) a set of several dozen novels, and (3) a corpus of historical newspaper articles. There will be a chance on the final day of the workshop for students to explore their own data sources if they so choose.
The focus of the workshop is to gain both a conceptual understanding of these techniques as well as achieving the basic programming skills required to employ these ideas in future research projects. Material is adapted from the instructor’s recent textbook Humanities Data in R: Exploring Networks, Geospatial Data, Images, and Text.
Getting Started with Data, Tools, and Platforms taught by Brandon Locke, Thomas Padilla, and Dean Rehberger, Michigan State University
Starting a digital humanities research project can be quite intimidating. This course is designed to make that process less so by exploring tools and platforms that support digital humanities research, analysis, and publication. We will begin by reframing sources as data that enable digital research. We will work throughout the week on approaches to (1) finding, evaluating, and acquiring (2) cleaning and preparing (3) exploring (4) analyzing (5) communicating and sharing data. Emphasis will be placed across all stages on how to manage a beginner 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 are reusable. Throughout this course, we will examine several existing projects, and move through the process of collecting, cleaning, and structuring humanities data and sources and plugging them into tools and platforms to analyze, visualize, share, and publish the data and analysis. Exploration of these stages of project-building will include a technical walk-through, as well as an examination of the tools and their underlying methodologies. Participants are strongly encouraged to bring their own research material to work with, but sample data will be provided.
High Performance Sound Technologies for Access and Scholarship, taught by Tanya Clement and Stephen McLaughlin, University of Texas at Austin
There are hundreds of thousands of hours of important spoken text audio files, dating back to the nineteenth century and up to the present day. Many of these audio files, which comprise poetry readings, interviews of folk musicians, artisans, and storytellers, and stories by elders from tribal communities contain the only recordings of significant literary figures and bygone oral traditions. These artifacts are only marginally accessible for listening and almost completely inaccessible for new forms of analysis and instruction in the digital age. Participants will be introduced to essential issues that archivists, librarians, humanities scholars, and computer scientists and technologists face in understanding the nature of digital sound education and scholarship as well as the considerable possibilities that building an infrastructure for enabling such scholarship and teaching can enable. In order to understand these issues, participants will be introduced to advanced computational analytics with sound such as spectrogram creation and annotation as well as clustering, classification, and visualizations with sound collections. In particular, participants will be introduced to open source tools such as Praat, Sonic Visualizer, and ARLO for use in research and teaching. Using collections of sound such as PennSound, the world’s biggest collection of freely available poetry performances, as well as collections that the participants are interested in bringing, participants will begin to develop use cases and curriculum in which they use advanced technologies to augment their teaching with and research on sound. Experience with teaching and research with sound collections will be assumed, although familiarity with digital sound analysis is not a prerequisite.
Humanities Making taught by Jeremy Boggs, University of Virginia and Tassie Gniady, Indiana University
The goal of this class is to introduce students to a number of practices associated maker culture in the humanities and to prepare to students to continue to explore the issues surrounding humanities making at their home institutions. We will learn about: 3D object acquisition via photogrammetry using Autodesk’s Memento (currently in beta) for stitching and cleaning of models, 3D printing with the goal of having each student print a model, and fabrication with simple electronics and wearables/textiles. We will also engage in theoretical discussions related to making so that reflection is paired with action. Questions for consideration include: What are best practices to employ in the classroom? How do these differ from research practices? What values are embodies by maker culture? How do 3D objects and their dissemination / placement in digital spaces change understandings of cultural heritage? What is the role of making in the humanities?
Humanities Programming taught by Brandon Walsh and Ethan Reed, University of Virginia
This course focuses on introducing participants to humanities programming through the creation and use of the Ruby on Rails web application framework. This course will introduce programming and design concepts, project management and planning, workflow, as well as the design, implementation, and deployment of a web-based application. Primary technologies covered in this course will include the command line, Git and GitHub, HTML, CSS, Ruby, Rails, and relational (and non-relational) data stores, though others will be touched upon briefly. Over the course of the week, we will work through the practical implementation of developing and deploying a small-scale web application.
Text Analysis from Object to Interpretation taught by Katie Rawson, Emory University and Scott Ebersole, University of Pennsylvania
While a range of freely available tools and excellent tutorials have made it easier to apply computational text analysis techniques, researchers may still find themselves struggling with questions about how to build their corpus and interpret their results. This course will approach text analysis from object to presentation. It covers not just the moment of feed-machine-text-get-results-back, but the process of managing materials and grappling with the meaning of results. Our class will be as much about the decisions and practices of text mining as about tools or step-by-step processes.
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; Present the results of their computational work to non-experts. We will use primarily off-the-shelf tools that you can download or access for free (though we will have one section that will make use of R or Python). In some parts of the course, you will be able to develop your own materials; however, we will primarily work together from shared data sets that the instructors will provide. This course will be appropriate for people at all levels of technical expertise. Students should have administrative rights to load R and other software on their laptop.
Sponsored student scholarships are available for undergraduate and graduate students as well as continuing professionals.
Group discounts of 5 or more attendees are also available.
Registration
Regular: $975
Early Career Scholars and Cultural Heritage Professionals: $775
Student: $550
Registration fees includes admittance to one course, the HILT Ignite and Social, and a HILT swag bag as well as breakfast and lunch in our campus dining hall.