Remi-Gau/eCobidas

split MRI and MEEG big spreasheets into small subsections

Remi-Gau opened this issue · 3 comments

goals

  • identify overlap between MRI and MEEG spreadsheet and extract those as core / common
  • create a new spreadsheet for each of the main section / activity of those spreadsheets: currently this "fragmentation" of the spreadsheet into activities was done by the python script. Breaking those at an earlier stage will make it easier to work with each individual spreadsheet.

workflow

  • to be done in the splitiing_process branch
  • this work will be done on the CSVs on there repo, so no work should be done on those main spreadsheets on the G drive
  • before the work starts the latest version of the google spreasheet will be pushed on the repo

to do

  • freeze the MRI and MEEG spreadsheet on the G drin (@Remi-Gau )
  • put the latest version of the MRI and MEEG csv on the repo (@Remi-Gau

Naming format for the spreadsheet

SectionName-modality.csv

# example

Participants-commom.csv

Acquisition-commom.csv
Acquisition-mri.csv
Acquisition-eeg.csv
Acquisition-meg.csv

@CPernet I don't remember the details of the naming format you suggested

To be discussed later

What level of "granularity" do we want to do the splitting at?

Let's start with the biggest chunks:

  • participant sample
  • experimental design
  • acquisition
  • preprocessing
  • analysis
  • results
  • data sharing

And then we'll take it from there.

@CPernet

I have done the splitting of the MRI and MEG spreadsheets.

The spreadsheets that are mri or meeg specific start with the mri- or meg- suffix respectively.

I think that there might be some work to see if there is some overlap between modalities that can be factored out in some core spreadsheet.

i couldn't locate the changes?? or is it on the google drive

I had to do a lot git branch juggling because of some old weird old branching pattern.

The things were committed here: 67ae208

If you :

git pull upstream master
git pull upstream splitiing_process

You should be good to go.