Between administration and research: Understanding data management practices in a mid-sized technical university
This repository holds code and data for the preprint Between administration and research: Understanding data management practices in a mid-sized technical university on SocArXiv.
The analytic pipeline for creating the figures is reproducible through the
drake package. Running r_make() will rebuild the analysis.
The pipeline is specified in the file R/02-plan.R. You can visualise the
dependencies with the following code:
library(drake)
source("R/02-plan.R")
vis_drake_graph(plan)All packages that are used during the analysis are specified in R/packages.R.
For the analysis files to render you will need to install the font "Hind" (for
example from Google Fonts) and
register it with
extrafont.
See the file load_fonts.R for specific instructions.
The figures of the final paper can be found in figs/final. This directory also
includes further figures that were not used in the paper.
Initial explorations can be found in general_exploration.html, as well as
in the directory figs/descriptive.
Core files for reproducing the analysis
| Filename | Purpose |
|---|---|
| _drake.R | Core file for building the analysis. Run with drake::r_make("_drake.R"). |
| R/00-packages.R | Lists and loads all packages relevant to the analysis. |
| R/01-functions.R | Functions that wrap preprocessing tasks as outlined in plan.R. |
| R/02-plan.R | Describes all inputs and outputs along with the functions processing them. |
The directory data/raw contains the raw files as they came from LimeSurvey.
There is one file with all respondents, and one with those that completed the
survey. It is not advised to use the file with all respondents, since some of
the respondents did not finish the survey by clicking "Submit". This drop-out
might be due to genuine loss of interest, or simply because someone wanted to
look at the survey without giving honest answers.
There was no substantial cleaning done on the survey responses, only tweaks
to the column headers. The result of this, and therefore the basis for the
figures, can be found in data/processed. This directory also includes an
overview of the variables in the survey, mapping short codes to answers.
Raw data files
| Filename | Purpose |
|---|---|
| data/raw/results-survey896447-total.csv | Raw data from the survey with all respondents. |
| data/raw/results-survey896447-total.csv | Raw data from the survey with respondents who finished the survey. |
| data/raw/label_basis.csv | Full headers, which are used to produce the overview of variables. |
Processed data files
| Filename | Purpose |
|---|---|
| data/processed/survey_processed.csv | Cleaned data from the survey. This file is the basis for the analysis presented in our paper. |
| data/processed/labels.csv | Plain language descriptions of the variables in data/processed/survey_processed.csv. |
You can find more information on the drake package here:
https://books.ropensci.org/drake/
The analysis was last rendered with the following package versions:
- Session info -----------------------------------------------------------------
setting value
version R version 4.0.3 (2020-10-10)
os Windows 10 x64
system x86_64, mingw32
ui RStudio
language (EN)
collate German_Austria.1252
ctype German_Austria.1252
tz Europe/Berlin
date 2021-01-21
- Packages ---------------------------------------------------------------------
package * version date lib source
ash 1.0-15 2015-09-01 [1] CRAN (R 4.0.0)
assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0)
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broom 0.7.2 2020-10-20 [1] CRAN (R 4.0.2)
ca 0.71.1 2020-01-24 [1] CRAN (R 4.0.2)
callr 3.5.1 2020-10-13 [1] CRAN (R 4.0.3)
cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.0)
cli 2.1.0 2020-10-12 [1] CRAN (R 4.0.3)
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dbplyr 2.0.0 2020-11-03 [1] CRAN (R 4.0.3)
desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.0)
devtools 2.3.2 2020-09-18 [1] CRAN (R 4.0.2)
digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.3)
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drake * 7.12.7 2020-10-27 [1] CRAN (R 4.0.3)
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