Tuesday, February 21, 2017

Data and Dimension- Pt. 2

Welcome back! If by some odd chance you've ended up here first, please click here to see part 1 of this blog post.


The second text that I'll be exploring this week is "Marking Texts of Many Dimensions" by Jerome McGann. Within the first few paragraphs of this article, I'm already lost in the meta nature of the text:
Consider the phrase "marked text"...How many recognize it as a redundancy? All text is marked text, as you may see by reflecting on the very text you are now reading. As you follow this conceptual exposition, watch the physical embodiments that shape the ideas and the process of thought. Do you see the typeface, do you recognize it? Does it mean anything to you, and if not, why not? Now scan away (as you keep reading) and take a quick measure of the general page layout: the font sizes, the characters per line, the lines per page, the leading, the headers, footers, margins. And there is so much more to be seen, registered, understood simply at the documentary level of your reading: paper, ink, book design, or the markup that controls not the documentary status of the text but its linguistic status. What would you be seeing and reading if I were addressing you in Chinese, Arabic, Hebrew – even Spanish or German? What would you be seeing and reading if this text had been printed, like Shakespeare's sonnets, in 1609?
Alright McGann, you have my attention.

This chapter in Blackwell's Companion is, much like "Databases," incredibly technical, although I expected this when I selected and paired the two together. As I mentioned above, DH is a technical field and I think it's important to have an introductory backbone that addresses how technical it can be.

Text markup involves the breakdown of language into words and even smaller units, in order to analyze the bits that work together to communicate ideas. This may sounds a bit scientific and don't be mistaken, it is. In face, McGann compares it to physics.
Words can be usefully broken down into more primitive parts and therefore understood as constructs of a second or even higher order. The view is not unlike the one continually encountered by physicists who search out basic units of matter. Our analytic tradition inclines us to understand that forms of all kinds are "built up" from "smaller" and more primitive units, and hence to take the self-identity and integrity of these parts, and the whole that they comprise, for objective reality.
I might even compare it to chemistry, studying the molecules that make up compounds in order to understand why the compounds act as they do. How interesting, to compare that to words.

In text markup, the objective is to instruct the computer to identify basic elements of natural language text, in order to understand the redundancy and ambiguity that is inherently tied to language. This is not unlike the example database Ramsey analyzes in the first article. He spends a good bit of time examining the redundancies caused by errors in the programming of his data. In this article however, we are finally introduced to the TEI, or Text Encoding Initiative, which I've come to learn is major in DH methodologies. The TEI system is, according to McGann, "designed to 'disambiguate' entirely the materials to be encoded."

This is still very murky and confusing. Luckily McGann backtracks a bit, and explains what he calls "traditional textual devices," in order to later unpack the intricacies of TEI and SGML- standard generalized markup language, the overarching title for markup languages. The power of traditional textual devices lies in their ability to make records of their progress and process these records without the use of technology.
A library processes traditional texts by treating them strictly as records. It saves things and makes them accessible. A poem, by contrast, processes textual records as a field of dynamic simulations. The one is a machine of memory and information, the other a machine of creation and reflection... Most texts – for instance, this chapter you are reading now – are fields that draw upon the influence of both of those polarities.
SGML, on the other hand, looks at texts through the scope of data and coding and uses these tools to process and record although the use of the tools requires a humanist to curate the work. TEI, more specifically, can be programmed to focus directly on things that stand apart, to mark them as different, so the humanist can later come in and analyze meanings that may be tied to.

It's at this point I realize I'm going to need to dial it back and come back to this article. The syllabus that I've been compiling for this course is an ever-changing being and, after getting about halfway through this article, I see that I need to find a more basic explanation of TEI and SGML. Despite reading through the article several times, I feel completely lost-- which just means I need to learn more, and go down another rabbit hole.

McGann does pull my interest back when he applies markup to the poem, "The Innocence," by Robert Creeley. Although I am murky on how markup is done, McGann's six readings through the text showed the different elements that come to light through markup, which wouldn't be immediately obvious otherwise.

Of his choice of this poem, McGann explains:
I choose "The Innocence" because it illustrates what Creeley and others called "field poetics." As such, it is especially apt for clarifying the conception of the autopoietic model of textuality being offered here. "Composition by field" poetics has been much discussed, but for present purposes it suffices to say that it conceives poetry as a self-unfolding discourse. "The poem" is the "field" of action and energy generated in the poetic transaction of the field that the poem itself exhibits. "Composition by field", whose theoretical foundations may be usefully studied through Charles Olson's engagements with contemporary philosophy and science, comprised both a method for understanding (rethinking) the entire inheritance of poetry, and a program for contemporary and future poetic discourse (its writing and its reading).
As I came to the end of this chapter, I found the appendices to be helpful in unraveling some of the more complex parts of the discussion but, overall, I think that I need to find a more basic reading that will start from square one of markup, so that I'll be able to build a stronger base understanding of the methodology. I knew I was in for a lot in this field of study, and the intricacies haven't scared me off yet!

As was the case with "Databases," I'm going to need some examples or practical application because the theory is quite dense, but it's incredible to know the things that can be accomplished when technology is married to the humanities. It certainly seems that the digital humanities use both sides of the brain, fusing logical and creative, to create something entirely new.


As a side note to this blog, it's going to be really funny when I read this later on and have a deeper understanding of DH, and see how much I'm struggling to unpack all of the theory

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