Materials on Image-Mining for Medical History

Last week, I taught the image-mining portion of the Images and Texts in Medical History workshop at the National Library of Medicine. I am far from an expert on OpenCV, the open-source computer-vision library. But as usual, that didn’t stop me from attempting to teach it.

The materials I created for the workshop include detailed instructions on how to use OpenCV to extract images from scanned journal pages (using a script written by Chris Adams), as well as a detailed breakdown of how to use the Python OpenCV library to take the average color of an image. I’ve also included links to my favorite resources on OpenCV and computer-vision in general. (My experience has been that there are a lot of really terrible tutorials out there, so I’ve tried to link only to those that are actually helpful.)

Ben Schmidt taught the text-mining portion of the workshop, and his materials are really great. His handouts in particular are concise, opinionated rundowns of the strengths and weaknesses of various forms of text analysis.

In preparation for the workshop, Ben and I created a virtual machine, provisioned via Vagrant with all the dependencies and data the participants needed. If you’d like to install the VM, it has everything you need for both Ben and my portions of the workshop, and the instructions should be pretty clear. (The VM is based on one that Andrew Goldstone created for his Literary Data class.)

The process of getting the VM installed on participants’ own computers was … complicated. We learned many things about Vagrant and VirtualBox, including the fact that Windows 7 and 8 don’t come with any way to handle SSH.

It was definitely the most technically complex workshop either of us have attempted (to a group of about 50!!). It was definitely not hitch-free, but it was really satisfying to see participants get excited about computer vision, and to talk about ways they might use these techniques in their own research.

A better way to teach technical skills to a group

a stack of orange, blue, yellow, and pink post-it-notes
“Post-It Notes,” by Dean Hochman

My DH101 class this year was my biggest yet, with 45 undergrads. I suppose that’s not huge compared with many other classes, but DH101 is very hands-on. I am fortunate enough to have a TA, the awesome Francesca Albrezzi, who runs separate weekly labs. Still, I often have to teach students to do technical things in a large-group setting, and the size of the class this year prompted me to rethink how I do this.

As I see it, many of my students’ biggest problem with computers is their own anxiety. Obviously, I have a self-selecting group, since I teach a class with “digital” in the title, but even so, many of my students tell me that they are just “not technical.” Many of them are so convinced of this that they see any failure to get something to work as confirmation of what they already knew: they’re just not good with computers.

And since this is UCLA, the vast majority of my students do not fit the stereotype of the Silicon Valley programmer. This is awesome for the class, since we have so many different voices in the room. But it also puts many of my students at risk for stereotype threat, in which students’ performance suffers because they fear their mistakes will be seen as representative of their entire race or gender.

I’ve seen a version of this happen in workshops countless times. The instructor issues directions while students try to keep up at each step. Some students accomplish each step quickly, but some students take a little longer to find the right menu item or remember where they’ve saved a file. No matter how often you tell students to please interrupt or raise a hand if they need help, most students won’t do this. They don’t want to slow everyone else down with what they’re sure is a stupid question. Eventually, these students stop trying to follow along, and the workshop becomes, in their minds, further evidence that they’re not cut out for this.

Continue reading “A better way to teach technical skills to a group”

What’s Next: The Radical, Unrealized Potential of Digital Humanities

This is a lightly edited version of the keynote address I was honored to give at the Keystone Digital Humanities Conference at the University of Pennsylvania on July 22, 2015. Thank you to the organizing committee for inviting me!

My sincere thanks, too, to Lauren Klein and Roderic Crooks for their advice and feedback on this talk. I’d also like to acknowledge the huge intellectual debt I owe to David Kim and Johanna Drucker, with whom I’ve argued, negotiated, and formulated a lot of these ideas, mostly in the context of teaching together. David’s important dissertation, Archives, Models, and Methods for Critical Approaches to Identities: Representing Race and Ethnicity in the Digital Humanities (UCLA, 2015), takes on many of these issues at much greater length.

I gave the title of this talk to Dot Porter some time ago in a fit of ambition, and it’s seemed wildly hubristic to me ever since. But it’s something I care a lot about, and so tonight I’d like to outline some ideas about how digital humanities might critically investigate structures of power, like race and gender.

We are doing some of that now, as evidenced by some of the work at this conference, but I don’t think we’re doing it with the energy or the creativity that we might. I’ll argue that to truly engage in this kind of work would be so much more difficult and fascinating than we’re currently talking about for the future of DH; in fact, it would require dismantling and rebuilding much of the organizing logic, like the data models or databases, that underlies most our work.

So I’ll start by saying a little about where I think we are with digital humanities now, and also about some new directions, with respect to these structures of power, that I’d like to see the field go.

Continue reading “What’s Next: The Radical, Unrealized Potential of Digital Humanities”

Humanities Data: A Necessary Contradiction

This is a talk that I gave at the Harvard Purdue Data Management Symposium on June 17, 2015, in Cambridge, Massachusetts. The audience was mostly librarians and other data-management professionals. I was the only humanities person on the program, so I wanted to talk about the ways that humanists think about data differently from people in some other fields.

Two mosaics beside each other. The one on the left is made up of largely cool, blue images; the one on the right is composed of warmer, earthier tones.
Sometimes I start class discussions by comparing image quilts of Google searches for “digital” (left) and “humanities” (right).

Today I’d like to talk about the ways in which humanists think about data, and how that’s distinct from the ways in which scientists and social scientists think about it.

Even though I think our issues can be pretty different, I want to make the case that there are some very promising ways in which libraries could make meaningful interventions in the humanities research lifecycle, both for what we might call traditional humanists and for digital humanists. So I’ll start with what “traditional” humanists might need help with and then move on to the needs of what we call “digital humanists” (although I think in practice the distinction is a bit blurred).

I just want to say at the outset that there are people who specialize in humanities data curation, and I am not one of those people. A number of talented people, including Trevor Muñoz at the University of Maryland and Katie Rawson at the University of Pennsylvania, have started to take a very programmatic look at the data-curation needs of digital humanists. And I encourage you to check out their important work. But you don’t have Trevor or Katie; you have me! So what I can do is share my own perspective and experience on what it means to work with data as a humanist, and where libraries can help.

Continue reading “Humanities Data: A Necessary Contradiction”

Reflections on my digital materiality and labor class

Group photo on top of One Wilshire.
DH150 on the roof of One Wilshire. Photo by Craig Dietrich.

I was really glad to get the chance to teach a special topics course on Digital Labor, Materiality, and Urban Space last quarter. I’ve been thinking about this class for years, and the syllabus is the (imperfect) culmination of lots and lots of reading and thinking.

In the event, the class was terrifically generative and fulfilling — for me, and, I hope, for the students. While the memory of the class is still fresh, I wanted to jot down a few notes about some new-ish (for me) elements I introduced into this class, and how well I thought they worked.

Continue reading “Reflections on my digital materiality and labor class”

Up and Running with

omeka logoYesterday I had fun teaching a beginning Omeka workshop at THATCamp Feminisms West, a really great event at Scripps College. (It deserves a post of its own, but that will have to wait until I have a little more energy. Alex Juhasz has a nice post about it.)

Omeka’s documentation is actually very good, but experience has taught me that students really appreciate handouts. So here’s a digital version of my handout for a beginning Omeka workshop.

I know a lot of people teach these workshops, so feel free to use or modify this material (PDF version, Word version) if it’s useful for you. And here’s a handout that offers a quick Omeka vocabulary lesson and some guidance on whether Omeka’s the right tool for your project.

I also have a post and handout on the next step with Omeka, creating an exhibit.

As an aside, I make these tutorials with Blue Mango’s ScreenSteps software, which I highly recommend.

[Edit: Thanks to Jon Ippolito, who tipped me off to this interactive screencast about building an Omeka exhibition.]

Continue reading “Up and Running with”

Use Automator to combine your research photos into one PDF

By request, these are updated instructions for using your Mac to combine your research photos into a PDF. For more on digital research workflows, see here, here, and here.

If you have a Mac, you own a robot! It’s called Automator and it lives in your Applications folder. It does pretty much what the name implies: It bundles little actions and makes them easy to repeat and perform on a lot of files. Here, I’ll show you how to use Automator to combine a bunch of research photos into one PDF.

Open Automator


It lives in your Applications folder.

From the pop-up menu, select Workflow


Choosing Workflow means that in order to run your series of actions, you’ll open up Automator first. (It’s kind of fun to experiment with Application, too! That means that to your series of actions becomes a standalone application. To run it, you double-click on your icon or drag some files onto it. But for now, let’s keep it simple and stick with Workflow.)

Let’s investigate!


The Automator interface is actually pretty simple. The far left pane (1) contains categories of actions you might want to run. The second pane (2) contains the actions themselves: things like “Add Songs to Playlist” and “Combine Excel Files.” You can assemble actions into sequences by dragging them from pane 2 into pane 3, in the order you want to run them. So, really, not too complicated!

Assemble your actions (1)


First, you need a way to feed Automator the files you want it to alter. Under the Files and Folders category in pane 1, find the Ask for Finder Items action in pane 2 and drag it into pane 3. This means that the first thing that Automator will do is ask you which files you want it to modify. Because you’ll be modifying multiple files, check the Allow Multiple Selction box.

Assemble your actions (2)


Happily, the latest version of Automator comes with an action that does exactly what we want! Under the PDFs category in pane 1, you’ll find an action called New PDF from Images. Select it and drag it into pane 3. In the Output File Name box, call it something that makes sense to you. You can even tell Automator where to save your new PDF, if you want.

Run your workflow


Click on the Run button, which you’ll find in the top right-hand corner of your Automator window. Automator will ask you to select the photos you want to modify (hold down Command-A to select all the photos in a folder) and then it’ll run your actions!

You’ve got one big PDF!


Unless you specified a different place to save it, your big PDF should be waiting for you on your desktop, simple as that. Cool, huh?

Save your workflow


Since you’ll probably want to do this again, select File, then Save, so you can perform these actions again later. You can save it as a Workflow, or, if you don’t want to have to open up Automator every time you perform your action, you can save it as an Application.

Play with some options


Automator does a lot of cool stuff, and it’s fun to just play around with it. For example, you can make your PDF easier to find with Spotlight by using the Set PDF Metadata action (in the PDFs category). Give it a shot! You won’t break anything.


The wind in the trees: Regimes of attention

“What the modern movie lacks is beauty,” said D.W. Griffith, melancholy at the end of the a long career, “the beauty of the moving wind in the trees.”

At film’s inception, it’s said that viewers didn’t necessarily know where to rest their eyes. Film hadn’t organized itself into the streamlined patterns of cause-and-effect that we recognize as narrative. Why not let the eyes wander to the wind in the trees?

An unspoken truth about early silent film is that it’s really hard for most people to watch for any length of time. At class screenings in grad school, we students would settle in with the best of intentions. But after an hour or so, having exchanged complicit looks, one of us would sidle up to the DVD player and press fast-foward. The damn things are silent, after all. We got the gist, even at double-speed.

The problem is that early silent film counts on a kind of attention that we didn’t have: an open-eyed fascination with the appearance of moving photographic images, and the ability to grasp allusions to any number of turn-of-the-century pop-culture references.

Having watched enough of these films, I can now, with a great deal of concentration, summon up a reverie that I imagine to be like the kind of attention early viewers brought to film. When I can, I do see things that I don’t usually see — my own equivalents of the wind in the trees.

I thought of all this because I’ve been following some of the talk around the blogosphere about concentration in the digital age:

In broad strokes, I agree with Sample. Having now done this digital work a bit, I can promise you that it does indeed require deep focus and intellectual energy. (And, let it be said, I think Olson’s piece is an example of the worst kind of academic concern trolling.)

I like the melancholy Griffith quote, too, though, for its reminder that we’re at a transitional moment in our mode of apprehending the world — far from the first, and assuredly not the last, but an important one. There’s beauty to be found in the new regime of attention (we couldn’t have had Vertigo without narrative), but there was beauty in the last one, too. I know Sample and Davidson would be the first to agree with this; I’m not actually disputing anything they propose.

This is just to say: I was drawn to silent film because its difficulty rewards a viewer with an unfamiliar kind of beauty. I probably won’t stop assigning longer papers and books, not because I think they’ll somehow prepare students better for the workplace or some such nonsense, but because there’s beauty in them, of the kind that comes from immersion in a different regime of attention.

Utopianism and its detractors

Alice in Wonderland reflected in a CD
"Digital Reflections," by seriykotik1970

This year, the American Historical Association’s annual meeting included a THATCamp, which I was happy to attend. Andrew Hartman, a professor at Illinois State University, published an interesting response, which I wanted to take a moment to address.

Hartman enjoyed himself but wondered if the scholars attending THATCamp evinced an unwarranted utopianism about the prospects of technology to transform the practice of history. It’s a good question, and an understandable reaction, but I don’t think it’s altogether accurate. First, I think that what Hartman understood as utopianism may in fact have been an attempt by the participants to make newcomers like Hartman feel welcome. If there’s a utopianism present at THATCamp, I think it’s more about the possibilities of new forms of interacting with each other, not the technology itself.

(As an aside, I think that for women this may hit a particular nerve. Digital humanities’ vaunted niceness is an aspect of the field I love, but for women in particular being “nice” is often read as an admission of intellectual inferiority. Some people can easily afford to be nice; for others, the cost is higher.)

In fact, as I’ve written before, technological utopianism bothers me a great deal for very personal reasons, and it’s a stance digital humanists have been quite active in countering.

More substantively, I’d like to respond to another of Hartman’s points: that while digital history is “an important new tool … it does not change the way we conceptualize the past.” I’d like to argue that it does, and in ways that directly counter the characterization of digital history as utopian. In fact, much of it has an activist project that, like Hartman, draws on Marxist theory.

Continue reading “Utopianism and its detractors”