As I was writing up the last post, I had several thoughts flitting through my mind that comprise this rather spontaneous post. First, I have been trying to learn HTML and CSS in hopes of writing a website and I was having a particularly rough time solving how to compensate for horizontal adjustment of the webpage in the browser’s screen. I finally stumbled upon the realization that if I put the entire website in a single compartment, using <div> elements, all of a sudden I was working with one object upon the background of the larger html backdrop instead of a multitude. That realization did not come easily, which is perhaps why it is still on my mind, but I was reminded of it when I was I was thinking about Placcius’s system of note taking. At first it seemed analogous to bytes on a modern hard drive but as I thought more about it, I realized that analogy could not work because of the re-scalability of a hard drive compared to the wooden closet with fixed dimensions. No matter how Placcius tried, he would have never been able to fit more notes in his scrinium than the internal volume of the space would allow. But with a hard drive, the ability to hold information is not dependent upon the physical dimensions of the space so much as it is the components that comprise it and the system that runs it. With this, like in CSS, information is less about the space it takes up and more about the nested elements in and out of it.
On the computer I can store information, like my keystrokes, on a word processor, which is then stored inside of a folder, inside of the space named “desktop”, inside more folders, until the hard drive’s overarching C: drive folder. The nature of the information has changed from being simply collected and stored in a similar location to being located within the same nesting element at the same level of address. If this idea is applied to a text, with the digital representation of the text as the C: drive folder, it will more adequately describe the multiplicitous nature of massive addressability. But in addition to the numerical increase it suggests, the advantage of nested elements then allows for a more discriminatory analysis of the contents. For example, if I wish to look at the webpage’s contents as a whole, the paragraph section, the header and table of contents together, etc, the nesting elements could be limitless and yet focus in on exactly the elements I wish to look at. Indeed, the ability to zoom in on these features may be the single most important feature of nesting elements for our purposes, since Docuscope creates nested elements similar to this through its use of Language Attribute Types inside of Dimensions inside of Clusters. With this ability of focus, a text’s elements may be easily and quickly studied. But at the same time, the capability that we have to zoom in on a text is much like the answer to the universe proposed by the Hitchhiker’s Guide to the Galaxy; simply that a computer can give us the answer but the question lies unknown.
And, like The Guide, I find myself agreeing that in order to know the question we must have a better process leading to it. In other words, we already have the diagrams in front of us and the tagged texts available to make any number of more diagrams but we do not have the understanding, beyond the mathematical processes, of how we got there. Take for instance, the Russian matryoshka dolls and Google Earth Engine (GEE). With a set of matryoshka dolls, we can explore each and every nested element in the group, from the largest to the smallest. However, we are limited by the physical stature of the dolls in answering questions like what is the next biggest doll when we do not have one or it does not exist. At this point we are in an infinite loop that is ignorant of what the next biggest or smallest doll is until we ultimately find one at which point we return to the original condition. In the case of the matryoshka, the limit of physical matter is the hindrance to any further study of its nested elements. In respect to GEE however, the tangible information does not appear to be a problem. It is billed as “a planetary-scale platform for environmental data & analysis” with “trillions of scientific measurements dating back more than 25 years”. What GEE has is a seemingly infinite resource of information and, by extension, nested elements for that data. But what does this suggest for our studies? I believe that GEE is not unique in the sense of the information and nested elements that it contains but rather in its approach of portraying this information in a meaningful way. I will assume that these trillions of measurements have been available for the last twenty five years in which case GEE is more about surpassing the data through addressability rather than creating any new data. The fact that this is case leads me to propose that we have enough information present to us through a physical manifestation of a text, like a book, and in a digitally tagged file of that text to carry us on. But what we do not have are tools like GEE that allow for a “planetary-scale” analysis of literature where we can zoom from a letter in a text to a hundred years of plays on the London stage. How we will get these tools, however, is yet to be seen.