Skip to content

DH, DB and DV: Digital Humanities, Databases and Data Visualisation

October 30, 2012

Last week, I spent some more time watching a selection of data visualisation videos. While a particular mention of data visualisation has been stuck in my mind following a recent class analysis of Alan Liu’s “The State of Digital Humanities: a report and critique”, where “an interactive 3D overlay” took “the user’s attention away from the historical archive of…works”, these videos sparked a particular question in my head. What can be said about data visualisation as an advanced form of accesible information/presentation/aesthetics v simplicity and straight foward data? When I read Anna’s recent post, “The Humanities Identity Crisis and its Pharmakon”, which discusses DH and its image, as well as “the mid-life crisis of the Humanities which has driven the movement in Digital Humanities forward”, I again began to ponder this subject and eventually decided to write a “log book” record of my train of thought.

On the one hand, certain types of data visualisation are an incredibly sophisticated way of presenting data and an enticement to many casual users. However, there are a contingent, often scholarly, who value a standard database with a plain style and see this as a pure form that is necessary to undertake a successful analysis of the stored information.

Firstly, an examination of the best characteristics of data visualisation is best carried by looking at some impressive examples. For this, I revisited websites such as The Information Is Beautiful Awards and found some new ones, Crazy Egg’s Heat Maps, the Web Trend Map, and Daden Media’s Datascape. I accessed a more general overview like Net Magazine’s top 20 DV tools. Finally, I took a second glance at Aaron Koblin’s presentation of possibilities which extend into the realm of digital art. Aaron Koblin describes data as “telling a story” and demonstrates how data visualisation enables this. Lastly, I used Tagxedo to get a hands-on experience of data visualisation itself:

After browsing through these websites, data visualisation emeraged as a great companion to a more functional style of analysis. It dawned on me that perhaps the two do not have to be mutually exclusive. Datascape, for example, claims to simplify data. Perhaps it comes down to the fact that some people work in a visually-orientated way and some do not. Visualisation is also slated as a distraction from the data, however when used with the appropriate database it can also help the user to navigate through an extensive minefield of information. For the more recreational user and casual researcher, data visualisation is like one of New Guinea’s birds of paradise – an abundant display of temptation to explore the data further. Perhaps a compromise needs to reached, where we all spend a lot of time and money in creating two versions of a database, which offer a “plain text or html” choice to suit all types of users!

The possible resistance to the application of innovative forms of data visualisation is heightened by the fact that DH moves so quickly. Dr Susan Schreibman succinctly noted that “huge changes in the World Wide Web…would instrumentally change the nature of electronic scholarship”. With technology, the world is always on the cusp of something. DH and data visualisation are in a constant state of motion. The latter is always moving into more advanced methods and using the newly developed tools. At one point during this first month of the Masters in Digital Arts and Humanities, somewhere among the rushes of videos, a reference was made to DH and the Kübler-Ross model, which means that although their will be stages of denial, a promising reward is the end result of acceptance. Data visualisation could also share creative writing’s motto of “Show, don’t tell”. To sum up the advantages of data visualisation, I will refer to Contagious Magazine who highlighted its practical potential, “So, data visualisation is now being forced to sing for its supper, matching aesthetic appeal with a potential for genuine practical application. For example, Doug McCune’s 3D visualisations showed the possibilities for mapping crime, which could then be linked to GPS-enabled police patrol cars to ensure city blocks were appropriately policed.”

As with all fields, academic or otherwise, there will those who cling on to what they know or what they deem to be “good quality” and there are those who will test new things and make improvements. While Professor Pannapacker (see “What’s in a Name?”) examines a redefining of “the nature of academic careers”, this could also be applied to DH as a whole. He quotes Julia Flanders, director of the Women Writers Project at Brown University’s Center for Digital Scholarship, who stated that “the professor as a paradigm obscures the ecology of the university”. Perhaps, it is time that we scuttle our ship and rethink our old ways. One thing you simply cannot argue with is a quote from Colin Ware, “On the importance of visual perception Colin Ware says: “The eye and the visual cortex of the brain form a massively parallel processor that provides the highest-bandwidth channel into human cognitive centers.”

I began this post with the intention of weighing up the advantages and disadvantages of data visualisation. In truth, I could have save myself some time if I had noticed this Hans Rosling video beforehand. In Rosling’s exhibition, the brilliance of data visualisation is unquestionable and entirely self-evident. After all, in what better way could he tell “the story of the world in 200 countries over 200 years using 120,000 numbers – in just four minutes”?

Texts cited

Liu Alan, “The State of The Digital Humanities: A Report and a Critique”. Arts and Humanities in Higher Education, 11.1 (2012): 1-34.
Dowling, Anna. The Humanities Identity Crisis and its Pharmakon. UCC. October 2012 Web.
Schreibman, Susan. Digital Humanities: Centres and Peripheries. TCD. May 2012. Web.
Pannapacker, William. “Big-Tent Digital Humanities: A View from the Edge, Part 2”. Chronicle of Higher Education, 58.5 (2011): A32-A32. Web.
Unknown. Most Contagious. 2010
2 Comments leave one →
  1. November 1, 2012 8:24 pm

    Very informative and insightful. so many links to explore. This is a great example of collaboration and shareing of information. the reference to Kübler-Ross model, “which means that although their will be stages of denial, a promising reward is the end result of acceptance” reminds me a little of a religious cult and therefore a little scary but I think I aggree with the basic premmise.

  2. Vince Murray permalink
    November 3, 2012 2:32 pm

    I thought you might find this website useful, its all about Info-graphics and Data Visualization
    Really liked your post, very interesting.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s

%d bloggers like this: