Following on from my previous post about my data workflow, I outline my basic writing workflow here. As mentioned in the previous post, I use Scapple as a tool to organise my thoughts, brainstorm, and plan my work, including basic outline for my write-up (background on the figure above).1
I start my initial drafts, particularly methods and results sections within RStudio, as it is where I do my data analysis and visualisation and it is simply easier to write about methods and results while they are being worked on.
First of all, I use Scapple as a tool to organise my thoughts, brainstorm, and plan my work (background on the figure above).
Most of the data I work with comes from structured surveys. The original raw data is usually entered and cleaned in Excel - primarily because virtually everybody knows how to work with Excel. Once the data is cleaned and ready to be analysed, I export them to .
Over the past two years I’ve used R within RStudio environment as my only data analysis/visualisation application for my research. For the most part I’m a self-taught R/RStudio user, and I’m quite pleased with how far I’ve come in terms of being able to do pretty much everything I need in terms of data analysis and visualisation, and a significant part of writing up using RMarkdown in RStudio. In terms of data visualisation in R, I guess ggplot2 is what everybody turns to first, and I’m no exception.
I have been using GitHub to collaborate/share data analysis (and a bit of writeup) with my co-authors/collaborators for the last year or so. As most journals now require (or at the very least recommend) submitting original data used in the analysis, alongside the relevant scripts/codes, during the manuscript submission process, I thought it was easiest simply to submit the persistent link to the GitHub repository containing all the data and the scripts/codes used in the analysis and visualisation as part of the manuscript submission.
BBC News wrote “Climate compensation schemes ‘failing to reach poorest’” covering our recently published paper from the p4ges project in which we analysed whether social safeguards that are meant to target the project affected persons (PAPs), often the poor and vulnerable groups in the community, actually succeed in doing so.
BBC Science & Environment covers the findings from our article on social safeguards in CAZ. Using an in-depth case study of one of the recent social safeguards implementation carried out to compensate the potential negative impacts due to the creation of a new protected area (which also has a REDD+ pilot project) in the eastern rainforests of Madagascar, we show that the identification of the PAPs was severely flawed.
As academic researchers we mostly worry about research ‘outcome’ as in ‘result’ — because that is what gets written about and published.1 However, it might take years sometimes to fully see the outcome of your research, especially when you are talking about impacts through Action Research, action that relates to changing institutions and social behaviours. I was involved in one such ‘Action Research’ while working in Sweden. Although we were only just beginning to see signs of impact of our research actions after more than two years of engagement, we decided to not just wait for it to manifest fully but to write about it, and try to get it published.