DHBSI 2017 (August 14th - August 18th) detailed schedule coming soon!
Instructor profiles available!
Apply to the Digital Humanities at Berkeley Summer Institute! Applications will be accepted on a rolling basis.
- Social science v. humanist uses of qualitative data
- What is qualitative data analysis?
- Taking a content analysis approach
- Taking a discourse analysis approach
- Data visualizations with qualitative data
Instructor: Chris Church
This workshop will discuss methods of retrieval, data set creation, cleaning, and visualization for network data. This course will explore what network data is, how it is structured and created, and how visualizations can be used for analysis, with a particular focus on how network analysis can be used in the humanities. Participants will learn how to use tools like OpenRefine for cleaning and transforming data and then will visualize data using Gephi, an open source tool for network analysis. Finally, students will prepare their network graphs for publication using Inkscape. No prior knowledge is needed. Students will have the option of working with either a course data set or their own data. Christopher Church, Assistant Professor of History and Co-Director of the Nevada Center for Data and Design in the Humanities at the University of Nevada, Reno, will lead this track.
Instructor: Rochelle Terman
This workshop will teach participants how to build a visually appealing, easy-to-use personal website in WordPress. Particular attention will be paid to building a personal academic site, such as those widely desired by graduate students entering the job market. No web development or design experience is necessary for attending this workshop.
We will first set up the hosting for our website with DreamHost. After hosting and the domain are configured, we will go over topics such as communication strategy, WordPress content architecture (posts, pages, tags, categories, media), free and premium themes, site building elements (widgets, menus, shortcodes), plugins and special features, and migrating your site. In addition to WordPress, attendees will learn to customize the design of their WordPress theme through acquiring a basic working knowledge of HTML and CSS.
Instructors: Patty Frontiera, Adam Anderson, and Susan Powell
This workshop will cover the basics of working with geospatial data and tools in digital humanities projects. Students will work through a sample project as a means for learning about and getting practice with:
Geospatial data fundamentals - concepts, data types, tools, and methods
Geospatial data management - data modelling and project design
Geospatial data creation - georeferencing, geocoding, digitizing
Geospatial data integration & processing - transformations and operations on the data to prepare it for analysis (data cleaning activities) and to answer basic questions. Creating linkages between data sets based on common attributes or location.
Geospatial data visualization - static and interactive (web) map creation and sharing these maps on the web
Geospatial data analysis - basic spatial queries and spatial overlay
Students are encouraged to bring their own data and will have ample opportunity to receive one-on-one consultation on their project.
Instructor: Scott Paul McGinnis
This workshop will impart lessons that I’ve learned teaching History 88 “How does History Count? Exploring Japanese American Internment through Digital Sources,” a connector course for the Data Science Education Program.
In History 88, students learned how historians use data in their research. The course began with two fundamental points: 1) a major part of historical practice is inquiry, and 2) to a historian, data are sources. Their in-class exercises and homework assignments consisted of a combination of data-intensive methods such as querying a database, and close reading of sources like handwritten letters. In all cases, the emphasis was on how to ask, refine, and answer historical questions with primary sources.
In this DHBSI workshop, we will go through some of the more successful exercises and homework assignments from History 88, with an emphasis on how they might provide models for use in other courses. Overall, the examples presented here should transfer well to courses in many fields of the humanities and social sciences, wherever there is a desire to combine digital techniques with a close engagement with primary sources.
Topics covered will include data collection and cleaning, managing a large group project, data visualization techniques, making use of UC Berkeley’s data science infrastructure, and how to balance technology and content. The workshop will demonstrate how several tools and skills may be used, but it will not require participants to do any of their own computer programming. For newcomers to computational techniques, the exercises will suggest a number of directions for further study and for collaboration with other faculty and graduate student instructors. For those with some programming experience, the course will provide various examples of how digital techniques can be applied to a classroom setting.
This workshop is intended primarily for faculty and graduate students who plan to develop Digital Humanities courses. No special computing skills are required.
Instructor: Laura Nelson and Teddy Roland
Increasingly, humanity’s cultural material is being captured and stored in the form of electronic text. From historical documents, literature and poems, diaries, political speeches, and government documents, to emails, text messages, and social media, students from the humanities now have access to immense amounts of rich, and diverse, text. This workshop will introduce students to cutting edge methods of analyzing and interpreting digitized text, in order to explore questions fundamental to the humanities. The ultimate goal is to encourage students to think about novel and creative ways they can apply these techniques to their own data and research questions, and to provide the skills necessary to apply the methods in their own research. We will use the open source (and free!) programming language Python and the Jupyter platform. We will also provide demonstration corpora.
- Introduction to Python for text analysis
- Principles of Natural Language Processing
- Identifying important and distinguishing words
- Dictionary methods
- Text classification
- Exploratory text analysis using topic modeling and/or word2vec
Students are strongly encourged to complete this brief tutorial to learn the basic syntax of the Python programming language prior to attending the Summer Institute.
Co-sponsored by the Berkeley Center for New Media.