Digital Humanities Axioms

These are a series of axioms I've come up with, based on some guiding principles I wrote down when beginning my virtual archive, Minor Works of John Lydgate. I believe that anyone who is working in digital humanities should have a similar set of guidelines -- if not expressly articulated, then floating around in the back of their head. I'll be adding to this as time goes on, I work on more projects, and I run into issues. This is meant to be an organic document rather than some sort of totalizing theory of digital humanities work; I may someday write something along those lines, but I doubt people want to hear it from me right now and to be frank I'm not sure many are interested in what I have to say in that regard. For that reason, these are mostly in place to help keep me honest.

  • Respect your audience. You're working with multiple groups of people with their own sets of expertise. You are the bridge between them and your work, so explain things in such a way that what came before is not lost in chasing what is to come.
  • Welcome the enthusiast. No, they won't know everything you do, and sometimes they will come with preconceived notions. That's ok. It's your job as the expert to help guide them to a greater understanding of the objects of your study and to be able to contextualize them within their own.
  • Whenever possible defer to the actual thing you're working from. Undue abstraction is bad, and leads to assumptions.
    • Know that the virtual facsimile is more and more likely to be the first way that people encounter these objects. Your facsimile should not present itself as the authoritative be all and end all, as it cannot be by virtue of being a facsimile. Provide enough for the curious, but also provide guideposts to those who want to go on to study the real thing.
    • It is all right to show the flaws in your model, so long as you explain why those flaws exist and what purpose they serve. Show your work, seams and all.
    • Digitization is inherently a process of creating a lossy version of the material, physical world. Make that clear to people. They should never think the virtual facsimile is a fundamentally acceptable substitute for the real object. It is always, always a "good enough" version.
  • Explain what you're doing. You are the expert, yes, but that doesn't mean you're infallible. The more abstract you are, the more you need to explain. You should never see a visualization or text displayed without both the underlying data and an explanation of what exactly it means. Someone who does not have a technical background needs to be able to follow both the scholarly and technical explanations, and it's on you to write in such a manner that they can. Examples are your friend, here.
  • Recognize that most digital tools are built for search and discovery, and always keep that in mind when working with them. If you want more than search and discovery, an off the shelf tool is unlikely to help you.
    • No digital tool can do the analysis a human can without some form of human intervention. Said intervention is always editorial, and needs to be explained up front.
    • IT tends to have a model of thinking that favors the near future; the next quarter or the next year. If you are a scholar you are doing work that should be expected to stand up to the test of time; your digital work needs to reflect this even if the platforms it is built upon change from underneath it.
      • You will always, always need to build crosswalks. There is no such thing as one ontology, schema, or structure to rule them all. Start planning accordingly; build it into your funding proposals and provide robust data dictionaries, annotated if necessary, to guide others in the ideosyncrasies of your project.
    • Be aware that people may lose data in moving into or out of your schema. That's part and parcel of attempting to capture the analog digitally. Avoid it as much as possible if you can, and if you can't then explain exactly what you did so others have signposts to recapture what's lost.
  • Use the tools that will be most efficient for you. Don't pick a platform or method because it's cool and new technically. Always go for the simplest method you can.
    • When choosing methods, platforms, and the like, simplicity is best but also be cognizant of the ways that those methods might close off avenues of discovery. Keep in mind that the decisions you make are baked in if you don't explain why you made them.
  • There should be no such thing as black boxes in your work. Transparency needs to be the order of the day in all of your dealings with code, with theory, and with people.
  • Remember that the technology is always secondary; you are first and foremost a scholar of medieval literature and culture. The technology is a way for you to explain that, not an end in itself. If it is getting in the way of getting the work done, then the technological solution is not the one to use. Set it aside and go back to the text.
  • Always have a way to get your data out.
  • Always provide something to explain your methodological approach. Don't assume people do things the way you do them; that something should be part technical, part philosophical, and part theoretical.