In Big-Life-Lab/bllflow: Big Life Lab Flow - a Workflow for Predictive Studies

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Introduction

Data and models are meaningless without good metadata. Metadata should be independently understandable; machine actionable; discoverable, dynamic, interactive. bllFlow uses consistent labels and metadata throughout the workflow. We explain why in our accompanying [document]. tl;dr Nature Videos

bllFlow_variables

bllFlow_variables is the data file that describes labels and metadata in bllFlow. Add to your own bllFlow_variables or make a pull request.

Labels and metadata are used in five key areas of research reporting:

1) Data cleaning and variable transformation -- such as applying truncation rules, centering, etc. 1) Aggregated results -- such as Table 1 - Characteristics of study population. 1) Model description -- model coefficeints. 1) Summary statistics -- metrics model performance. 1) Validation data -- example dataset to verify algorithm scoring (for predictive models).

bllFlow_variables

library(DT)

dt <- read.csv(file.path(getwd(), '../inst/extdata/bllFlow_variables.csv'))
datatable(dt, options = list(pageLength = 5))

Big-Life-Lab/bllflow documentation built on Feb. 1, 2023, 12:29 p.m.