SCRIVENER AS A RESEARCH TOOL
I want to underline that Scrivener is a powerful app also for research. It can store directly all sorts of file formats from varied sources of information, indexes instantaneously the stored information, uses a most dynamic search feature that helps to classify and aggregate the information, can serve as notetaking application. Stapple, its companion app, can be used to provide a first design of the information and give a helicopter view of the structure of the project.
With excuses for the length of this post, I hope these ideas can help in some way.
I. IMPORT OF RESEARCH INFORMATION INTO A SCRIVENER PROJECT
1. Where to import
I import all sort of research materials (doc, odf, webpage, pdf, txt, etc., etc., even films and voice recordings -including my own voice notes) into the research folder (or into a sub-folFer of it, or into a new root folder (and eventually sub-root folders). This folder will become in fact a (portable) database of my research sources.
2. Devices to use
You can import the materials into your project using all sort of devices: pc, laptop, tablet (ipad), smart phoen (iphone). Online imports with portable devices are synchronize via Dropbox; thus, automatically, if you will.
3. Source of the research materials
The source of those materials can be other files in my laptop, in Dropbox, web (amazon book pages, google books, etc.), etc.
4. Auxiliary Applications to collect the information
To collect (import) the mentioned information, I use almost exclusively Scrivener and the applications that are already embeded in Apple OSX and iOS, and in the web engines. Share, export, print, open or save files in specific formats (docx, odt, jpg, etc.) are now possible without needing to make use of -for instance- Evernote (an application and intermediate step that -having Scrivener and all the embedded applications- I finally came to experience as superflous and cumbersome).
To write my notes I use what is at hand as embedded application in OSX, iOS, Android, etc., no matter what kind of notetaking app: Scrivener can suck and eat almost every kind of file format (and if I do not want to open Scrivener for the document to be imported, I simply store it in a dedicated folder in Dropbox, to later be imported into Scrivener).
The only external application I use for research is DevonThink (an excellent file management app which combines very well with Scrivener). DevonThink can index all or part of the files of the disk, and can aggregate them into dynamic groups resulting from search, without touching the original files. But it is not really an indispensable application, especially if using Scrivener. I use it simply because prior to my using of Scrivener, I had collected mountains of information corresponding to the most disparate sort of subjects, a lot without any relation to the research project. It would we crazy to import all those files into the project, and DevonThink serves thus as a sort of first filter of that accumulated information.
II. SELECTION AND AGGREGATION OF INFORMATION MATERIAL
The selection and aggregation of collected information material depend on the phase (advance) of the research.
1. Search and Storage of the Information Material
Initially I have only a vague idea of the content of the research. I collect the material thus according to a very general, pre-conceived classification. I import the information into the research or other folder (created as mentioned above).
I assign the imported documents some (also, in general, preconceived) tags, on the basis of a first inspection/reading of the collected information. This can be done in Scrivener using, for instance, keywords and custom metadata. In this first phase I do not try yet to classify the information into groups, even if I immiddels have already developed a richer, more definite structure of my research (to be reflected in the binder); tags are at this moment not (or rather, should not be) a real criteria of aggregation.
A very important element to be used when storing information is the index card of each document, a digital card. where you can quickly store the general write down a short synopsis of the document, and some other data, as i.e. keywords (keywords you better create in metadata, but this is maybe a bit slower than filling the information in the index card).
2. The aggregation of the Information Material
2.1. I make the first aggregation of the information into different groups using the really powerful search function of Scrivener (further than a mere -but very fast- search functionality, it also contains other functionalities that make it a powerful research tool).
2.2. The search term can be any word of a document, tag, etc. The result of the searches produces groups of document that you can store as static of dynamic collections; the static collections do not change their content when importing new information files.
2.3. The DYNAMIC COLLLECTIONS, on the contrary, update automatically the content of the group when new imported files or files in (if you so determine) any other folder of the same project. They can be created, and updated automatically, throughout the whole live of the project, while keeping the original documents in the folder where they were originally stored; but you can also edited the documents in the collection, and the changes will be reflected in the original file and viceversa.
Dynamic collections, I find, is the most powerful instrument to begin the structuration of the information and, to a large degree thus, is the main auxiliary tool to determine the first structure of the final draft (obviously, it can also help to redefine the structure of the draft in ulterior phases of the research). Successive aggregations begin to give an idea of the extension of the subject of research, etc., providing the elements for a first structure of the research (to be improved in the course of the research). From seed to embryo, to root; and all of these transformations are carried out within and with the tools of Scrivener!
III. ZOTERO
- I use Zotero as bibliographic tools. But apart from the difficulties of handling it from within Scrivener, I found that when incorporating a great number of files, it was taking too much of my time to insert the required information into its different fields.
- For the time being (until, I hope, a tool is developed to sync between Zotero and Scrivener), I simply make a short reference to the source document in the footnotes of the project; later in the product of compiling (Word LibreOffice Writer, etc.) I will convert those short references into Zotero references (in many or most cases, I will only then produce the records in Zotero that correspond to my references in Scrivener. It is a slow process, but I prefer to resort to it because I cannot be sure whether some errors have been introduced when resorting to the RTF scan method, especially with a high number of footnotes. I have seen some errors happen in my texts, and read about something similar in several blogs.
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It is not necessary to go further than wha I have outlined above. The aim of this text has been, as mentioned, to show how from the very initial steps of a research, Scrivener can serve as a most powerful instrument of research.
