During this semester, we’ve understood data to mean numerical facts and statistics. Scholars can represent those descriptive numbers and aggregations along two dimensional coordinate systems and maps, communicating an understanding of the texts or medium under study by abstracted details into summaries. Contributions like Manovich’s Exploring One Million Manga Pages with Supercomputers and HIPerSpace “ use visualization and/or mathematical models to describe the space of possible and realized variations” by clustering the amount of gray scale or measuring the level of detail in illustration among 1,074,790 pages. Others employ methods like distant reading to process words and sentences in large corpora as way of confirm the coherency of writerly social characteristics, and ponder the examples which evade their models (see So and Roland’s stellar Race and Distant Reading). These flavors of analysis view data as a means push away from subjective knowledge of artistic output, proposing dimensions and measures as appropriate tools for grappling with humanities as scholarly sport. The quantization champions of digital humanities offer mostly rigorous and often legitimate intellectual insight to their subjects of study. Still, there is a more capacious views on data, a more digitally native observation, beyond the statistical definitions we’ve been exposed to this semester.

CUNY’s own Kevin L. Ferguson stands as starting point for many members of this minority group of data “analysts.” Looking at his frequently updated tumblelog Film Visualization, it’s easy to mistake his methods as art (in fact, he courted some controversy when an artist appeared to ape his methods). As a part of his scholarly work, Ferguson produces summed frame visualizations. Screenshots of a movie are superimposed on themselves by loading them into the open source medical imaging software ImageJ, provided by the NIH.

While comparisons on the corpus and categorical level are made by “automatic process which reveals otherwise unconscious information about film texts” (DHQ: Digital Humanities Quarterly: Digital Surrealism: Visualizing Walt Disney Animation Studios) what differentiates these summed frame ouputs from more common visualization methods is two fold. Firstly, this method takes digital data, in the form of images, as material from which to create a subjective understanding of the objects under study. While there are numerical transformations involved in the production of these images, the artifacts generated require context and knowledge of the specific films under analysis, and are not summarized by statistics. Contrast, color and framing of subjects can be determined for each movie, or for the movies of a corpus, but the visualizations themselves are only a component in the over all conclusions one can draw. Secondly, these summed frames suggest a mode of experiencing or “reading” that is more embodied than typical distance reading. The scholar may see a perpondance of close-ups in a given corpus rather than talling the number of such shots, or may observe the lack of vue variation in a color film.

Another digital humanist with an expansive view of data and its expression is Kim Brillante Knight. Her project “Danger, Jane Roe!”, described here, cleverly grounds itself in a tradition of feminist praxis. Knight fashioned embrodery of reproductive anatomy undergirded by LilyPads, a flavor of Arduino microcontroller for wareable technology. Little LEDs light up in the decoration based on how many #prolife hashtags are posted on Twitter over a specified period of time. Knight links the projects to many linages of practice.

The adoption of decorative textiles, an artform fogged by traditional modes of feminitity, for a politically potent topic is one example. Leaving the application stitching visible by using a contrasting color with the reproductive organs “can make explicit the workings of a circuit” more visible by implication, implying “polarity, connectivity, and flow” that most digital hardware products obscure. A key aspect emphasized in the wearing this visualization on the body is to “remov[e] data visualization from the screen or page…relocates discourse around reproductive justice onto the site of legislative inscription—the body that may be affected by pregnancy.” If you read the article linked above, you’ll be treated to a thick fabric of theory and practice that legitimizes what could be glossed as an non-academic pursuit if you aren’t considerate or don’t read the whole article. As it relates to an expansive sense of data, we can appreciate an embodied experience of data that has it’s origin in technology on the screen, but seeks to escape it. Once can imagine a version of this wareable, perhaps untenable for long periods of usage, that vibrates when a word from a hashtag dictionary is posted. Imagine that as an embodied experience.

Writing about a large sense of what data can mean in a digital humanities project leaves to invigored by how many potential new modes and methods are left underexplored in a field. Digital humanities, in whatever manifestation or metaphor of organization, seems to experimentation and not wedded to received ideas of scholarship, which I find appealing.