Making of the Humanities V
Society for the History of Humanities
Johns Hopkins University, Baltimore
Oct 5–7, 2016
ABSTRACT The digital humanities present new possibilities for applying computational technology to humanistic inquiry, for better understanding the role of that technology in our world, and even for rethinking the nature of the humanities and what it means to be human. Many authors (Hockey 2004; Svensson, 2009, 2010, 2012; Kirschenbaum, 2010; Dalbello, 2011) date the emergence of this field to 1946 and Roberto Busa’s Index Thomisticus, an IBM-sponsored project encoding the works of Thomas Aquinas on punch cards for search, retrieval, and analysis. From there, the history is told in terms of text and linguistics, with the plot revolving around corpora of increasing size and susceptibility to machine analysis—until quite recently, when digital humanities is suddenly said to be a “big tent” (Pannapacker 2011a, b), encompassing everything from digital archives and databases to GIS, network analysis, new publishing formats, digital pedagogy, game design, and so on. How did this narrative come to be, and what counternarratives does it exclude or constrain? This paper presents an empirical perspective on the early history of digital humanities by tracing publications in two foundational journals in the field (Computers and the Humanities, established in 1966, and Literary and Linguistic Computing, established in 1986), focusing on the disciplines of their authors and of the works those authors cite. Analysis of this corpus—and its evolution—reveals points of similarity and convergence across the humanities and, tangentially, the social and applied sciences, painting a broader and more inclusive picture of the digital humanities than has been presented to date.
Keystone Digital Humanities Conference
Kislak Center for Special Collections
Rare Books and Manuscripts at the University of Pennsylvania Libraries
July 22–24, 2015
ABSTRACT In the past few years, nearly two dozen degree and certificate programs have been developed in the digitalhumanities, with more announced each year. Existing studies have examined course syllabi and assignments (Terras 2006, Spiro 2011) and the development of specific programs (McCarty 2012, Sinclair and Gouglas 2002, Smith 2014). In addition, there are critical discussions in the field as to the role of common standards in digitalhumanities (Spiro 2012), the proper balance of skills and critical reflection (Clement 2012, Mahony and Pierazzo 2012), and relationships to the work force. To date, however, there are no systematic surveys of existing degree and certificate programs. Such studies would contrast earlier work, which often seeks the invisible structure of digitalhumanities as revealed through analysis of its disjoint parts, and offer an empirical perspective on debates about DH pedagogy.
This presentation analyzes and visualizes the location, structure, pedagogy, and other features of formal DH programs, with particular emphasis on questions of disciplinarity, methods, courses, and skills. To reflect the broad and varied nature of digitalhumanities, this study uses the crowdsourced TaDiRAH (Taxonomy of Digital Research Activities in the Humanities) to code the activities referenced in the curricula and to present aggregate results about common goals and competencies of DH programs. This analysis explores the differences between “one-off” DH classes and sustained study of the field across successive, intentionally-grouped courses. The presentation concludes with critical reflections on these DH programs in light of pedagogical concerns expressed in the literature.
Lexis maps (also “Lexis diagrams”) are used mainly by demographers to show population trends over time. (I’ll explain below how to adapt them for other kinds of data.) They combine elements of scatterplots (quantitative values and individual data points) with the benefits of a heatmap (intensity coloring of some trend). Demographers like them because they drill down on aggregate population trends (e.g. birth rate, death rate, morbidity rates) to show how events affect different segments of the population at different ages. This one shows the baby boom of the 1950s and 60s through female birth rates from ages 14–49.
Though few have heard of them outside of demography, Lexis maps can handle the complex type of data that visualization was meant for: quantitative, longitudinal, high-density, multivariate data. Most Lexis diagrams span a hundred years or more for ages 0–100+, resulting in tens of thousands of data points in a single display. As others have put it
Lexis maps might be compared to a lavish Chinese banquet, whereas the graphs over age and time are more like a delicate Japanese dinner (Vaupel, et al 1998).
Given all this, Lexis maps have great potential, and I’m hopeful we’ll see them used in interesting ways beyond demography (I’m still a big fan of demography). To help that along, I put together this workflow for creating Lexis maps in Tableau Public, a free version of the software used by places like the New York Times and Gallup. Tableau Public publishes web-based interactive displays that are sharable and embeddable in HTML—and it has a great video tutorials.
If you want to skip straight to the Tableau instructions, click here.
Background
Lexis maps are often attributed to Wilhelm Lexis’s 1875 proposal for diagramming population trends by birth cohort (though apparently they were proposed earlier). The basic idea is to model each person as a line beginning with their birth and ending at the age of their death. Putting all of these together at yearly intervals, you get birth cohorts for the population, which move together through time and are affected similarly as they move through time—more similarly even than other people who live through the same event, but experience it at different ages. Even a massive historical event such as World War II affects people differently; some are drafted, but others are too old or too young, and the event affects them in other ways. The same might be true of pregnancy or some disease. Model all of this on two axes (time x age) and you have a Lexis diagram.
This Lexis map shows the probabilities of death for Italian males, with historical events (e.g., WWI, WWII) clearly reflected in the population patterns.
Lexis maps can also be adapted to a variety of domains beyond demography. For example, I’ve used them to study gender ratios in publication rates of academic philosophers (treating PhD date as “birth” or entry into the field).
The visualizations above were created with Kirill Andreev’s Lexis Map Viewer, which was last updated in 1997 and requires Windows 3.1 or higher. Though the software is still great at what it does, it’s relatively obscure in the wider visualization world and outputs only static images.
After playing around in Tableau a bit, I realized that I could create Lexis maps using a symbol display, with the added benefits of interactivity, filtering, and more color options. Here’s a Tableau Lexis map of Italian mortality rates for the same period as the first graph above, with some annotations highlighting trends. You can also hover over individual data points to get exact probabilities for any cohort in a specific year. (The original graph uses cohort data from Natale and Bernassola (1973) and Caselli et al. (1985). My dataset comes from the Human Moratality Database, so there may be slight differences in the data.)
Below, I’ve outlined the key steps for making Lexis maps in Tableau Public, in hopes that demographers and others will be able to make use of this free tool.
Data Format
As with other datasets, Tableau requires normalized (not crosstab) data. There’s a great post on how to shape your data for Tableau, but most demographic data comes readily formatted.
Tableau Instructions
To make a Lexis map in Tableau, set up your worksheet as follows:
Columns: This is your variable for year—be sure to set the options to Dimension and Continuous.
Rows: Your variable for age. Again, this does not have to be natural age; some other examples might be grade level, or time from graduation. Be sure to set the options to Dimension (not sum) and Continuous.
Detail: The variable of interest—in my case, probability of death, q(x).
Marks and Size: Set the visualization type to Square and adjust the size so that each data point is just large enough that there is no white space between them (the smallest auto size usually works).
Filters: If you want to allow people to filter by year or age, add those variable to Filters and set them as Quick Filters. I put those below my graph so they are present but not distracting.
Color: The trickiest part. I realized that Lexis Map Viewer doesn’t use a linear scale for color, probably to highlight changes in trends more clearly. To replicate this effect, I created a calculated field on my variable of interest (right click on the variable) and computed the log of my variable, q(x). I used this new calculated field for Color, and chose a temperature diverging scale with 18 steps (the same number used in the original graph). If you want a smoother display, use more steps or turn off stepped color.
Tooltip: Finally, set up your Tooltip to display the information you want on hover. Since we use the calculated field and not the actual variable, I added that to Detail first (as Attribute), then I customized the Tooltip by removing the calculated field and adding my variable, q(x).
Summary
Overall, your Tableau worksheet should look something like this
And in case you were wondering, here’s what Italian female mortality looks like:
Vaupel, James W., Wang Zhenglian, Kirill F. Andreev, and Anatoli I. Yashin (1998). Population Data at a Glance: Shaded Contour Maps of Demographic Surfaces over Age and Time. Odense Monographs on Population Aging, 4. Odense University Press. http://www.demogr.mpg.de/Papers/Books/Monograph4/start.htm.
For the past two years, I’ve asked my DH graduate students to create a public, curated digest of tweets about digital humanities. We create these digests using Storify and post them weekly during fall and spring semesters. Many students find this tool useful (esp. for organizing and archiving conference tweets), and delving into Twitter discussions gives them an invaluable perspective on the field, given how much DHers like social media. More importantly, I like that we can turn this learning opportunity into a public resource from which others can benefit.
After several semesters, I learned that this online work needs to enter into our in-class discussions as well, so I started asking students to begin each class with a short presentation of their digest and a discussion of its contents. We get to hear why students chose the tweets they did, and the whole class can make links to current and former readings and projects they’ve seen. At times, I’m able to add more context to something that’s posted, and all of this helps students get a hands-on sense of how the DH community works.
Usually, each student signs up for one week, giving us coverage over the whole semester. This spring, I have a small section, so I presented several options on how we might pull things off. One of my students suggested that everyone pick one day each week to monitor Twitter (I agreed to take one as well) and that we publish the digest jointly as a class. I was thrilled at the collaborative aspect of this suggestion and added that we should begin each class with a half-hour project meeting where we review and discuss the tweets nominated over the course of the week and package up the digest for publication. There’s already been some side-chatter about this week’s digest on Twitter, and I think it’s a sign of good things to come.
You can follow @DHtrends or check out our first digest on Tuesday around 3:30pm EST at http://storify.com/DHtrends, and I’ll report back later in the semester on how our new collaborative model is going.
Every semester, students tell me that diving into DH can be daunting, especially because of the diversity of the field—there’s much to learn, much to read, much to play around with. I also suspect it’s harder for LIS students because their programs are not squarely grounded in a humanities discipline and they don’t have the same domain/content background, research questions, or intellectual support as humanities students. LIS professionals also have to facilitate work across various humanities disciplines, making specialization impossible in every case.
Here are my top five recommendations for LIS graduate students (and others) who want to become familiar with digital humanities:
(1) Read TaDiRAH, the crowdsourced taxonomy of digital humanities activities, objects, and techniques.
(2) Subscribe to dh+lib or follow @dhandlib for a weekly roundup of recommended readings, resources, posts, calls for papers/participation, jobs, and more.
(3) Join ACRL’s DHIG listserv (Association of College & Research Libraries’ Digital Humanities Interest Group), where members share info and discuss current issues in their DH work.
(4) Follow @DHtrends, a weekly digest of DH tweets during fall and spring semesters, curated by students at Pratt SILS.
If you’re interested in how to foster DH work on your campus, I have some suggestions in the conclusion of my article on DH and libraries.
For more advanced reading, the Journal of Library Administration published a special issue on digital humanities in 2013 and open-access articles are available through the following links:
This course examines the notion of community within cultural heritage institutions and the larger framework of cultural informatics. Particular emphasis is placed on social media as a tool for communication, engagement, and action. Topics include communities and digital commons, user studies, diverse populations, media studies, digital identity, social networks, information ecologies, social media adoption and use, community building, social advocacy and activism, and technology in the service of democracy.
Case study (40% final report, 10% each monthly deliverables)
Topics
1. Introduction
2. User Studies and Communities
3. Online/Offline Communities
4. Research Methods & Ethics
5. Research Conferences
6. Community Informatics
7. Strategies for Community Building
8. Social Media: Theory and Demographics
9. Research Day
10. Resistance to Social Media
11. Social Media in LIS Environments
12. Civic Engagement & Political Action
13. The Information Society
14. Case Study Workshop
This course examines the history, theory, and practice of digital humanities, paying special attention to the ways in which digital humanities are transforming research, disciplines, and even the academy itself. Topics include contrasts and continuities between traditional and digital humanities; tools and techniques used by digital humanists; the processes of planning, funding, managing, and evaluating digital humanities projects; ways in which digital humanities impacts scholarly communication and higher education; and the special roles of libraries and information professionals in this growing movement.
This course examines the art, science, and practice of information visualization. Particular emphasis is placed on the ways in which position, shape, size, brightness, color, orientation, texture, and motion influence perception of information and facilitate comprehension and analysis of large and complex bodies of information. Topics include cognition and visual perception; the aesthetics of visual media; techniques for processing and manipulating information for the purpose of visualization; studies of spatial, relational, multivariate, time-series, interactive, and other visual approaches; and methods for evaluating information visualizations.
This course examines the art, science, and practice of information visualization. Particular emphasis is placed on the ways in which position, shape, size, brightness, color, orientation, texture, and motion influence perception of information and facilitate comprehension and analysis of large and complex bodies of information. Topics include cognition and visual perception; the aesthetics of visual media; techniques for processing and manipulating information for the purpose of visualization; studies of spatial, relational, multivariate, time-series, interactive, and other visual approaches; and methods for evaluating information visualizations.
This course examines the history, theory, and practice of digital humanities, paying special attention to the ways in which digital humanities are transforming research, disciplines, and even the academy itself. Topics include contrasts and continuities between traditional and digital humanities; tools and techniques used by digital humanists; the processes of planning, funding, managing, and evaluating digital humanities projects; ways in which digital humanities impacts scholarly communication and higher education; and the special roles of libraries and information professionals in this growing movement.
