This is wrong in so many ways, but I just couldn’t resist this #ds106 assignment.
Richard Stallman photo from Cool Picture Gallery.
Hot Dog image shared by abi728 at Clker.
This is wrong in so many ways, but I just couldn’t resist this #ds106 assignment.
Richard Stallman photo from Cool Picture Gallery.
Hot Dog image shared by abi728 at Clker.

Some rights reserved by mutednarayan
The past few weeks of my digital research seminar has been spent trying to define the digital humanities and the role English academics can play in this hybrid field. Most of the us in the class have little technical experience with digital media beyond the interface. As a result most are reluctant to identify themselves as digital humanists, even if they study digital artifacts.
Last night, though, we had an engaging discussion about Critical Code Studies from a pedagogical perspective. Two texts in particular, Michael Mateas’s “Procedural Literacy: Educating the New Media Practitioner” and Mark Sample’s “Criminal Code: The Procedural Logic of Crime in Videogames” provided the foundation of this discussion.
These texts were well received because, for once, collectively we felt comfortable entering the DH conversation. This was odd since we identify ourselves as non-programmers. According to Mateas, procedural literacy is “the ability to read and write processes, to engage procedural representation and aesthetics, to understand the interplay between the culturally-embedded practices of human meaning-making and technically-mediated processes.” This was promising. If code is indeed an expressive medium that calls into question the role of authorship, audience, aesthetics, and such; then we do have something to offer.
Mark Sample’s piece gave us an opportunity to discuss how non-programmers might approach procedural literacy. Sample’s text examines the procedural rhetoric of crime in the game Micropolis. He argues that a close reading of underlying code can teach non-programming students how code can conceal and regulate human-interaction.
From this discussion, some interesting questions were brought up.
Here are a few:
While some students were still reluctant about teaching CCS without prior knowledge of a programming language, everyone understood the potential of engaging with procedurality. Those who were most reluctant likened the teaching of code to the discomfort of teaching grammar to ENC1101 students. While we didn’t get to definitive answers to the above questions. We understand that these questions are important and need further attention.
In Loss Pequeno Glazier’s article “Code as Language” he argues that code is a language because it is a technology of representational inscription that is dependent upon expressive “combinations and patterns” to communicate meaning.
In developing his claim, Glazier points out that encoding, like alphabetic writing, utilizes space to produce meaning. Just as the formal document structure informs the reading of an alphabetic text, so too does the digital rely on spatial structure to form meaning. He explains that in e-texts the spatial qualities of the computer screen, networked interaction, and the distribution of data on the hard drive are crucial to the production of meaning. In programming language, he notes “space has functional, representational, and symbolic levels of meaning.” These things make it possible for interaction with the Graphical User Interface (GUI).
Noting that it is commonplace to think of digital media as immaterial because of its intangibility, Glazier highlights two issues that support this perception of immateriality—the spectral and dynamic nature of digital media. Because the digital art object is mediated by the computer screen and lacks a “fixed” quality, it is perceived as immaterial. However, Glazier contends that digital art objects, specifically e-texts, produce inscriptions on hard disks using mark-marking peripheries such as keyboards and mouse interaction. Like alphabetic texts, code is representational inscription, following grammatical and syntactical structures. Digital inscriptions provide “algorithmic thinking” not only in the composing process, but also in the process of interaction. Its inscriptions also have the unique ability to be copied into new contexts and are easily disseminated. These material qualities of the digital, Glazier suggests, are “highly specific in its historic and material circumstances.”
Reiterating his earlier claim that encoding is a process of composing, he highlights the ways in which encoded representational marks are writerly. According to Glazier, encoding follows specific grammar and semantic rules in the process of mark making and, therefore should be considered a form of writing. Encoding is also expressive and “meaning emerges through the process of engaging the medium.” Glazier also points out that coding errors or constraints can produce surprising results in the process of composition.
Glazier acknowledges that print texts indeed are in part event and invention, but he attempts to illustrate the possibilities of dynamic digital texts. Here he is contrasting static literary work of print to the dynamic work of the digital art object. For Glazier, it is necessary to understand the underlying code that produces the “shifting illusion of its surface.” In this sense, he is suggesting that writing code involves a rhetorical act. For Glazier, the term dynamic text should not be mistaken for the mere opposed of “fixed” texts. Instead, he suggests, “dynamic text seeks to engage that delicate edge where language apparatuses meet, slip, and engage, to further the possibilities of the poetic text.”
To demonstrate that code is poetic writing, Glazier addresses the digital poet. He suggests that programming will unlock the potentialities of the digital medium. Here he separates the digital poets, who focus on the “surface content,” from those poets with knowledge of the underlying code. For Glazier, there is a poetics at work in code, an expressive, literary layer that is often overlooked. As such, he suggests that a deeper understanding of code is needed.
I’m still working with DoD’s Operation Enduring Freedom data. Here, I decided to plot the number of soldier causalities by home state using Processing. The tutorial I’m following is from Ben Fry’s book Visualizing Data.
The map includes a mouse rollover function. I like the function because it allows viewers to interact. Though, I think there is a slight lag when the mouse hovers. I’m still in the process of learning the program, but it is a lot of fun. Next, I’d like to divide the map into red and blue states.
Check it out:
*You will need Java to view the mapped data.