Using DEVONthink for Literary studies. Round Two

I go the exact opposite from you – all my research is in DT, because that’s the only way that its power can most fully be harnessed. (I know Indexing offers most of that power, but I prefer to trust to the simplest option and import).

I’m an academic teaching and researching medieval and renaissance literatures. I certainly do all you refer to in your post, working on 1 history of lit; 2 literary theory; and 3 analysis of single works.

To come back to your original question, it’s worth remembering that DT is a fairly bespoke tool. I work in an academic department of c. 45 colleagues – all of them talented literary scholars working at the cutting edges of their fields. I’d bet you my DT license though that I am the only one using DT as my daily driver (see here for related discussions and some notes on my set-up, and those of others). I’d be delighted to meet more DT enthusiasts in the wild!. What I mean is that much ‘literary studies’ is conducted in a huge variety of ways, more or less tech reliant, and that much of the core of the discipline has little to do with how we organise our information. But of course, we have an enormous amount of it, and I personally believe that DT is among the best solutions to find a way through the morass of primary and secondary evidence.

I love DT for organising searches and fixed-data set searches (I like to create subsets of resources via Smart Groups, pulled into there via tags, and search these apart from everything else). I’ve had huge success recently with both scattergun approach (big, unwieldy search terms yielding tons of results), and the pointed search query that got me ONE hit. Just so happened to be the one thing that eluded me, and which set me off on a research path that answered many questions. But the key is that I curated a library over many years: way too large to keep fully in mind, but nevertheless consciously shaped according to my (narrow, in comparative terms) research activities, questions, projects, and so on.

In your original posts you floated a few ideas: e.g. using DT and dump in ‘the complete corpus of English Renaissance literature’. This could now be achieved more easily than ever before, but I’ve had little success with this despite the now free availability of EEBO-TCP: https://textcreationpartnership.org/tcp-texts/eebo-tcp-early-english-books-online/ (essentially transcriptions of the largest part of books printed in England and in English from c. 1470-1700). I think the issue may be that this database is in XML format and there are better tools than DT for wrangling large amounts of XML. There is also, simply, a huge amount of noise. It’s probably also more efficient to use the custom online repositories for searching these texts (but EEBO is, of course, behind a paywall).

Finally, I have found that effective note-taking of many ‘factual’ resources (esp. secondary criticism; historical background) lends itself very well to solutions like DT, and my personal note-taker of choice, Obsidian (which I have closely integrated). But I have never quite managed a satisfactory workflow – in the tech-sense – for note-taking and annotating poetry. The poem is such a dense object; repays constant re-reading; often lives in old editions (that I increasingly try to digitise these days to enable e-annotation); and somehow, and despite working ‘in the field’ for 15 years now, I still find effective research on verse a challenge. I think that this is because meaning emerges differently from a poem than from other types of text, and that meaning, moreover, is entirely context/question specific, and so will change over time as I (the reader) and my questions change. There is also the constant scaling of approach: I want to say something about an entire 154-sonnet sequence, say; but also about a single metaphor in line 4. Perhaps it’s simply the case that no amount of thinking about a literary text can ever be fully documented and/codified, and no literary text can ever be fully known, in order to be ‘done with it’ and enter it into our PKMs for instant retrieval.

Happy researching!

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