Open asizemore opened 2 years ago
I'm going to feature one variable, EUPATH_0011996::Sample type, because it's my favourite variable, and I'll link the commit here so that it's clear how to do it.
If there's ever a variable V in studies S and S', such that V should be featured in S but not in S', then it's gonna be a problem because we have no technology allowing that. But otherwise you'll just be able to feature whatever variables you want!
Thanks @wbazant !! Sounds like a great plan!
If there's ever a variable V in studies S and S', such that V should be featured in S but not in S', then it's gonna be a problem because we have no technology allowing that.
Ooh good to know, thank you. Tagging @dpbisme as an fyi
I'm not seeing the featured var on any study. @dpbisme do you?
Not crucial for beta release.
reopening because it failed qa. Note that this is not crucial for the b59 beta release. Will pick back up after b59.
Moving to b60 must haves
is_featured
needs to be filled out on a per-study basisAs of b62, some studies have featured variables, but @dpbisme is hoping to add featured vars to all studies for b63
Dan's list of vars to be featured can be found here: https://epvb.slack.com/archives/CBLPK9ZD3/p1677987475497809
Anopheles albimanus
Bangladesh
Bee Microbiome
BONUS-CF
CAMP
DailyBaby
DIABIMMUNE
ECAM
Eco-CF
Experimental Cutaneous Leishmaniasis
FARMM
GEMS1 Case Control
HMP phase I (V1-V3)
HMP phase I (V3-V5)
HMP phase I (WGS)
Human Cutaneous Leishmaniasis
MAL-ED 0-2yr
MAL-ED diarrhea
Malaysia helminth study
MORDOR phase I
NICU NEC
PIH Uganda
Preterm infant resistome I
Preterm infant resistome II
Uganda maternal
Featured variables in the EDA are variables that always live at the top of the variable picker in their own special box, so that it's easy for a user to see them (and star them) immediately. This view of featured variables is the same wherever the variable picker is seen - from the Subset to the Visualize to the Downloads tab.
The way we're doing it right now is that each study has it's own list of featured variables. From Danica: "I’m not sure if the way clinepi does it will work for mbio. We have an annotation property in the .owl for each study, which is called “is_featured”. we leave this blank for terms that are NOT featured, and fill in “yes” for variables that we want featured"
Doing this for mbio would address the goal of "pre-starring" variables that we think are interesting.