A break from our regular programming, this is the second in an occasional series on processes and tools (first post on creating your own maps here).
Here’s my academic writing workflow: it allows me to quickly pull together information from dozens of articles into a structured format that allows new ideas and connections to form. It won’t work for everyone, although there is plenty of scope for customisation.
1. Pulling everything together
I won’t go into great detail here, but I collect all my research materials together first. For me, this is PDFs of articles, reports, and book chapters. I use Papers for Mac and group everything into project folders, although there are plenty of other research managers: Zotero and Mendeley are free. Google Scholar is invaluable for sourcing articles (Papers allows you to search Google Scholar and import articles from within the application).
2. Highlighting and commenting
I now read through everything in rough order of how important I think the article will be. This means later articles can be skim read (when concentration levels are lower) to pick up additional insight or nuance. Whilst reading I highlight relevant paragraphs or sentences – as less is better try to avoid highlighting entire pages – and add comments with any thoughts or ideas. Papers has this function built in; an application like Skim (open source for Mac) can also do this.
3. Exporting and tagging notes
All highlights are now exported as plain text files – one per article or report, or a single file with all highlights across all readings. The beauty of highlighting in an application like Papers or Skim is the automatic inclusion of page numbers and other bibliographic information in the exported file.
Depending on the complexity of the project, I may just export all the notes as one giant text file, print this, and start writing. However, in more advanced literature reviews, for example, an extra step is helpful. In this case, I export each reading as an individual file (one click in Papers) and import these into TAMS Analyzer, an excellent open-source Mac application for qualitative text analysis. Effective use of TAMS Analyzer is a post in itself, but the documentation is fairly solid.
I then work through my imported highlights, and tag them. Usually this will be within 4-5 headings that will naturally emerge from the initial reading: for a recent review of universities and place, for example, I had the headings ‘leadership’, ‘international’, ‘regional’, ‘urban’ and ‘conclusions’. Finally, with a couple of clicks, TAMS Analyzer can generate a table with headings at the top, and all of the highlights below – one box per highlight. The source name – drawn from the plain text export of your initial highlights – is appended (usually Author-Year).
The great benefit of this extra step is a single file that can easily contain insight and analysis from twenty or thirty articles (or more). Instead of thirty print outs, you have one – admittedly quite big – file with several thematic groupings, each with a mixture of authors and sources. This makes writing much, much easier.
Again, I won’t go into this too much, as most people have their own tools and preferred way of working. I use Ulysses for Mac, which works fantastically for academic writing (more here). Citations are easily managed via Papers (or any other research manager), which sorts all the references and bibliographic information once the final text is exported into Word. Using the Magic Citations tool you insert references as you write (the source name, Author-Year, is in your table from step three).
I work through the table of notes as I write, often sequentially by thematic heading. This has two main benefits: you’re drawing on notes ordered by theme not author, so you naturally avoid paragraphs with multiple citations from the same source. Second, with excerpts from many sources sitting next to each other in the table, you make new connections between different authors and ideas. Any notes or comments you made on the initial read through are also included.
This workflow mimics a paper method I used years ago, which took a lot more time (and a lot more paper). Some may prefer to read from paper copies – I tend to print just the most important articles. Others prefer to write as they read.
For those working outside the social sciences this workflow may not work so well – but I’d be interested to test this. It doesn’t work so well with books unless you have a PDF version, although these are often cumbersome. I tend to take notes on books outside of Papers, and save these as a text file to be used in step three.
Lastly, the flow in workflow is important. If you wait too long between the first few stages and stage four (writing) you begin to lose the connections you form when you make the initial highlights. The wider context of selected sentences is lost, and you forget why you highlighted certain sections in the first place.