The data-ness of knowing from qualitative fieldwork

I've been asked to offer some thoughts on fieldwork and data collection at a BricoLab meeting tomorrow, thought I could use this space to ruminate. 

Not everything one comes across during fieldwork is "data". I think qualitative fieldwork is incredible because it produces profound knowledge about settings and phenomena. If one truly knows something they can write conceptual or theoretical pieces about it all day long. However knowing the phenomenon is not the same thing as having data about the phenomenon. And I am ultimately an empiricist and I need data. I also want to recognize that its not as simple as data/not data. Its not a binary. I believe there is a continuum of data-ness of knowing from qualitative fieldwork, along the dimension of reflecting + encoding. 

Let me try to explain what I mean by that...

You come out of a session in the field, an observation session, and interview, whatever. You are buzzing with excitement about what you have discovered, you know new and exciting things about your phenomenon, moreso than you did before the session. But that's not data.

After the session, you take a look at your jottings in your field notebook, made in the heat of the moment, and now your memory of the session crystallizes. Certain elements are foregrounded. You may even made a few additional jottings that in retrospect are significant. Bit data-ish now.

That evening you record some reflections about your experience in the field. Charlotte Cloutier strongly suggests that you write your field notes (distinct from live jottings) the same day as your observation session. That is ideal, but maybe you have a seminar to prep for the next day, or dinner to make, and there isn't the time for typing down field notes. An audio reflection is a good middle step, and we all walk around with phones that can record and transcribe voice. Iterative refection makes your data even more data-ish.

Soon (yes, SOON) after, you type something down. This isnt merely a transcript, either of the observation session/interview, nor is it your audio memo, though those certainly is helpful to have. This is a written reflection, either as typed fieldnotes or as a typed data memo, discussing some specific things you saw or heard, contextualizing them within your broader study. At this point, your automated transcripts have been manually curated as well, you have made choices about including and excluding audio and visual artifacts. Encoding data lends it some data-ness. 

Next you have organized your encoded knowing- your fieldnotes, your curated transcripts, your photographs, sample document, physical artifacts, etc. into folder and subfolder. Systematicity increases data-ness.

Now you have an active tally of number of interviews and field sessions, hours in the field, minutes of recorded interviews, pages of field notes and transcripts, archival texts, etc. Maybe you even have a handy-dandy automated ready-to-drop-in-a-manuscript data summary table. Reportable metadata makes your data quite data-ish.

Finally, deep in analysis and writing, you have  curated your data. You have excerpted vignettes and quotes, you have organized them by category or over time, based on your judgement, based on what you think matters to a study. Agentic cuts produce the reality of data.

You can take it one step futher even, by associating data with theoretical vocabularies. You create artifacts intended for your discussion section, where empirical constructs have been mapped to theoretical concepts. Connection to theory means your data is ready to travel.