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Summer Workshop II Overview

Posted in DH Blog

Workshop II: What is Data?

“Data” and “humanities scholarship” may seem incongruous.  This workshop dispels that myth by showing humanities scholars not only how to find and use data, but how to re-see our research as data.  This workshop includes presentations by UO colleagues on data collection and visualization followed by visits by representatives from resources around campus who can help us build or data-based projects in our courses and research.


Announcements: Digital Humanities Program Communication

DH @ UO Website:

This site will serve as a resource for the UO DH community. You’ll find information about the minor in DH (currently under construction), DH course descriptions, faculty involved in the DH program, a descriptive list with links to faculty and graduate students digital projects, and campus support services for those who wish to set up or develop a project.

DH @ UO Blog:

You can access the blog from the site above or from the main DH website (  This series of summer workshops initiates the blog. We’ll publish weekly blog posts with reviews of current print and digital scholarship, pedagogy ideas, and announcements about campus events (workshops, lectures, etc.).

Forthcoming: the DH Listserv:

This new discussion list is open to the public. It’ll serve as a dedicated space for members of our community who wish to post announcements, questions, or reach out to others working in similar areas. You’ll find the sign-up link on the DH Webpage. We hope the listserv will help to feed a vibrant community network on our campus. You can sign up on the home page of the DH website:

Important DH Resources:


We began by thinking about data.  We looked at a few points made by Lisa Gitelman and Christine Borgman and Lisa Gitelman.

“At first glance data are apparently before the fact: they are the starting point for what we know, who we are, and how we communicate. This shared sense of starting with data often leads to an unnoticed assumption that data are transparent, that information is self-evident, the fundamental stuff of truth itself. If we’re not careful, in other words, our zeal for more and more data can become a faith in their neutrality and autonomy, their objectivity. Think of the ways people talk and write about data. Data are familiarly “collected,” “entered,” “compiled,” “stored,” “processed,” “mined,” and “interpreted.” Less obvious are the ways in which the final term in this sequence—interpretation—haunts its predecessors. . . . Data need to be imagined as data to exist and function as such, and the imagination of data entails an interpretive base” (3).

Lisa Gitelman, “Introduction” to Raw Data” Is an Oxymoron (Cambridge, MA: MIT Press, 2013).


“Data do not flow like oil, stick like glue, or start fires by friction like matches. . . . The unstated question to ask is, “what are data?” The only agreement on definitions is that no single definition will suffice. Data have many kinds of value, and that value may not be apparent until long after those data are collected, curated, or lost. The value of data varies widely over place, time, and context. Having the right data is usually better than having more data. Big data are receiving the attention, whereas little tickles of data can be just as valuable. (4)

Christine L. Borgman, Big Data, Little Data, No Data (Cambridge, MA: MIT Press, 2015).


“A healthy intellectual community depends on the vigorous pursuit of knowledge by scholars in high-energy physics and high Tibetan culture alike. The challenge is to develop knowledge infrastructures that serve the diversity of ideas, questions, methods, and resources that each contributes to scholarship” (15).

Christine L. Borgman, Big Data, Little Data, No Data (Cambridge, MA: MIT Press, 2015).


From there we learned about networks and visualizations from Helen Southworth and Matt Hannah.

We spent time looking at networked data on the Linked Jazz site

Kristi Potter introduced us to two wonderful DH resources:

Poemage and the Petrarch Project


Heidi Kaufman walked through the process of identifying and visualizing “small” data from subscription lists of a nineteenth-century novel.

We concluded with a visit by several people from around campus who want to help us set up and work with digital tools and resources:

DSC: John Russell

Infographics: Ken Kato

CMET: Helen Chu and Karen Matson

CASIT: Garron Hale


Thank you for joining us in the workshop and for following this blog!  We hope you’ll continue reading new blog entries and that you’ll join us for future workshops.



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