O rocks! Tell it to us in plain images (A THATCamp/Bloomsday Visualization)

Some results from the Bloomsday hack session, where we discussed small digital Joycean projects we might take on that day and continue working on over the following weeks:

We decided to create a dataset that could be used in Gephi to make something both informative and pretty: a log of the social interactions among characters that could be turned into a social network visualization. Chad Rutkowski read through the Wandering Rocks episode and logged a list of character interactions, which I then turned into a dataset and manipulated in Gephi to produce (click image for larger version):

Wandering Rocks visualization

Character nodes are weighted by the number of edges touching them (i.e. by how many interactions with other people a given character has), so unsurprisingly for anyone who’s read Ulysses, Father Conmee appears as one of the most connected characters in the episode.

Our next step will be to answer some questions about types of character interactions and include these answers in our dataset:

  • Do we want to log the direction of an interaction to cover cases where, for example, and conversation is one-sided? (Yes, but this means creating two edges for every dialogue: Bloom > Molly as well as Molly > Bloom).
  • What counts as an interaction? (Telegrams, letters, overheard shouts in the street?)
  • How do we handle time? (Is Bloom > Molly recorded only one time in our Ulysses datatset, or every time they interact? If the latter, how do we decide when an interaction counts as ended?) If we can find a satisfactory and non-insanity causing way of coding this, we could create a time-lapse visualization of interactions in the novel, perhaps with some sort of cumulative or heatmapping feature.
  • How to handle different types of interactions? We discussed assigning different numbered weights to interaction edges so that its easy to see the degree of interaction taking place (was a character imagining a conversation with Bloom, or actually talking to him?), but there’s some difficulty in deciding what types of interaction are deeper than others in order to place these on a spectrum and make visual apprehension easier.

Ben Schmidt also did some neat and quick work with the Circe episode, running a script to gather character names by grabbing the all-caps words in that section and mapping interactions stepwise by linking the names that appears next after a given character in the text.

We’ll continue working on this project as we have time, so if you’re interested in helping out, send us a tweet! The work involved is pretty easy: identifying a section of the novel you wish to attack, then making a list of the characters who interact and ID’ing the type of interaction according to a scheme we’re using.

Cross-posted from LiteratureGeek.com.

Display JPG2000 Images

JPG2000 holds the promise of lower storage costs for large collections of scanned documents. It can also minimize the bandwidth requirements for display the image details.

One limitation is that most web browsers do not support this format and thus would require a viewer.  Omeka does a good job of creating thumbnails from JPG2000 images, but you would still want to view the image at the full resolution.

Any suggestions on a good JPG2000 viewer / plugin that is able to handle multiple pages documents.

Digital Journalism and Digital Humanities, United

As I blogged a few months ago, it has become increasingly clear that digital humanities has a kindred spirit in digital journalism—perhaps a stronger potential relationship than humanities computing and computer science. We have discovered the same needs in terms of tools and infrastructure, and find ourselves engaging the public with similar genres of online writing and communication.

Just some of the products of digital journalism we could discuss or adopt at THATCamp: the 20 open source Knight Apps, which include DocumentCloud; what’s coming out of Mozilla OpenNews; and the developer challenges and tool reviews from Duke’s Reporters’ Lab.

O rocks! Celebrating Bloomsday DH-Style

Saturday is Bloomsday! It strikes me that we might put our DH nerdiness to more direct Joycean use than simply deciding which Ulysses t-shirts to wear. I propose using this post space to discuss possible small-scale, collaborative Joyce-celebratory projects we might undertake during free time throughout the weekend (not a session necessarily, but a backchannel collaboration). These could be performative (e.g. recording readings of favorite passages? maybe a choral reading? making a small game?) or investigative…

One possibility: I’ve been playing around with the free visualization tool Gephi recently; we might create a simple dataset representing one-to-one character interactions in Ulysses or part of Ulysses–who interacts with whom? How many degrees of separation does the most removed character have from Bloom?–and drop it into Gephi to create a pretty and useful visualization. This would require

1) People signing up to list all the character interactions for a given section in Ulysses (if we only have a few people, we could just divvy up pages in a single rich episode like Circe or Wandering Rocks). For ease of collaboration, it probably makes sense to use the Project Gutenberg e-text (unless the rumored new digital edition drops in time for us to use!).

2) Defining what an “interaction” in Ulysses entails (dialogue? glimpsing someone? thinking about someone?). Or are there other factors we might want to model with a visualization?

3) Creating a basic spreadsheet with two columns: whenever an interaction happens, create a row with Person A on column 1 and Person B in column 2. Unless we decide on doing a one-way directed sort of interaction–e.g. Bloom thinks about Molly doesn’t mean Molly thinks about Bloom at the same time–it doesn’t matter which person in a pair of interacting characters goes in which column. We might also consider adding a “weight” column that keys different weight numbers to “degree of interaction” (e.g. degree of 1 indicates thinking about someone, 2 indicates glimpsing but not being seen, 3 indicates dialogue). I can post a link to a Google Spreadsheet with example rows if people are interested; you might also check out the Gephi sample datasets looking at character interactions in Les Miserables and the Marvel comic universe.

Interested? Or have any other Joycean ideas?

Staring at the Gaps: A Hazy Session

I have a big, squishy, ill-formed, hazy thought about a thing, so where better to start my first-ever session proposal for my first-ever THAT Camp?

For many of us working in early periods, the further back we go the more gaps there are in the record, be that literary, historical, cultural, scientific, or what-have-you. I’m fascinated by those gaps and what can be found by tracking them and their surroundings. I sat in recently on a presentation by some undergraduates who were trying to map the social networks around Inigo Jones and his Jacobean masques. One of their frustrations (amidst some great success) was that it was impossible to tell exactly the nature of some of the relationships they had found. To me, though, that gap in knowledge seems like an exciting point to start from as we are working out the shapes and uses of digital tools in representing knowledge.

We can hypothesize about the ur-Hamlet from references that surround it, though the text is lost. We strongly suspect there was a Love’s Labors Won because of cultural materials that gesture toward it. So what else is hiding in the gaps back there? And how can new methods of representing the relationships between texts (since I’m a text person), between events, between people expose both the gaps and the context that surrounds them?

I’m thinking about gaps most particularly in two mapping contexts:

  • First, figuring out how early modern dramatic texts relate to each other—there’s so much allusion and reference happening between 1585 and 1630 and I really want a better way to think about how the plays reach out to each other and what might come into focus (both presence and absence) if we could visualize those relationships.
  • Second, can we use the conventions of geo-spatial mapping to think about generic cataloging? My primary example is revenge tragedy, which seems especially self-aware of its tendencies toward specific features. How might we begin to map out what the genre looks like and what kinds of gaps might exist in that map? Could a more representational approach to genre help avoid the anachronism that often occludes an understanding of how the texts position themselves?

Mapping/Spatial tech idea session

Hello all,

First, let me just put it out there that this is my first THATCamp, first unconference, and first post to this blog.  I’m a PhD Candidate working on a diss that will hopefully have some awesome digital aspects.  I’m looking at Baltimore merchants from about 1790-1830 and I want to do several things with my data.  First, I’d like to map the relative locations of merchants in Baltimore (I have pretty specific info from city directories) over time.  Second, I’d like to map their Atlantic networks, which will connect to Europe, the Caribbean, and South America.  Third (and this one is only a small possibility) I’d like to map the flow of goods by volume, similar to these maps.  What I’d like to achieve in this session is a set of ideas about which applications or methods would be best suited for what I want to do, and, to see if it’s realistic for me to tackle this much digital work for what will be a mostly traditional dissertation committee.

Help a grad student out! (that should be a category)