The Desolation of Data Entry

4 Oct
Desolated

Desolated (Photo credit: Moyan_Brenn)

I’m still plodding away on my data compilation for spiritual warfare manuals. It’s slow business, partly because there is little way for me to automate or outsource the work. Expertise is required to identify relevant data, and my coding chops aren’t quite up to the task of automating data entry yet.

On Twitter I saw an interesting DH link that led me to UCLA’s Center for Digital Humanities’ excellent online DH 101 course. As I prepare for the American Academy of Religion’s first THATCamp, I was meditating on the disconnect between my interest in digital humanities for religious studies and the expectations of appropriate and career-building CV-level production.

It’s a natural challenge for digital humanists. The academic context remains a print world. Even if I were tempted to say the humanities is well on its way to a text world (both virtual and physical), this isn’t necessarily true for tenure portfolios. Nor is it necessarily true for job applications.

Part of the challenge is that partial data can be not just confusing but misleading. I’ve shared some of the architectural or structural details of my data before. And while I’m committed to conducting as much of my research openly as I can, there are hurdles that I continue to trip over.

As an academic working outside of the academy for the moment, I worry especially about access and copyright. Thankfully I purchased many of my primary sources. This doesn’t mean, however, that I can treat them callously. How much data is too much data to extract from a text? If I collect all the bible verses cited in a spiritual warfare manual, have I exceeded fair use for the material? What about collecting printed transcriptions of ritual actions from these items for my database? (Many of these items contain testimonial examples. I’d like to be able to compare them side-by-side and tag their elements.) There are no hard and fast rules. And outside of the academy, I am personally responsible for any errors I may make.

To make fewer errors, I encourage folks to look at UCLA’s course, which covers many of the essential elements of DH. I encourage enthusiasts of every level to check it out. If you’re already familiar with DH and coding, then you’ll breeze through it in no time at all. If you’re unfamiliar with DH, then this is an excellent resource.

Where the site doesn’t do a great job is explaining the daily tasks of DH production to its audience. In part this is because DH are makers. If you’re a maker you implicitly understand that the daily task is to work on the thing you’re making. It can feel like a very long time until all the brushstrokes finally appear as a portrait though. The only way to really go from data through architecture to visualization or presentation is item by item.

It all reminds me of a Vulcan logic game featured in Star Trek: Voyager called Kal-toh. Players take turn placing pieces into a nest of rods to bring increasing order to the system. One move can win the game, bringing clarity, symmetry, precision, order, and structure to the chaos. Here’s a spoof video showing  what the game looks like:

I fear my DH hopes rest on some magical piece I was play somewhere down the line. I know I shouldn’t lay hope on such a piece. It’s probably a fiction. In fact, it is most assuredly a fiction. The process of compiling and organizing my data is an intellectual venture. It’s just one that is hard to represent or even write about well. And that’s the point, right? If the data made sense in some other way, then you wouldn’t need it to be visualized or placed into a database. The act of categorization is the intellectual heavy-lifting.

Just as I said in my response to Altman on Eliade yesterday, Eliade was brimming with interpretation. Categories are interpretation. Is this religious or not? What kind of ritual is this? It’s not for nothing that creationists bristle against a much wider range of science than simply human evolution. The very categories that evolution erects to describe its data fundamentally structure the interpretation of vast worlds of other information. Eliade may have focused on the thing itself for the value it had for itself, but in practice he selected the terms of valuation.

This may seem like a small distinction, but DH architecture says it is everything. Thus I move slowly and carefully along with my work. I plod because it keeps me honest about my motivations and decisions, which help me justify the way my structures will later produce interpretations worth the effort.

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