dataquieR
The goal of dataquieR
is to provide functions for
assessing data quality issues in studies, that can be used alone or in a
data quality pipeline. dataquieR
also implements one
generic pipeline producing flexdashboard
based HTML5
reports.
See also
https://dataquality.qihs.uni-greifswald.de
You can install the released version of dataquieR
from
CRAN
with:
install.packages("dataquieR")
The suggested packages can be directly installed by:
install.packages("dataquieR", dependencies = TRUE)
The developer version from GitLab.com
can be installed using:
if (!requireNamespace("devtools")) {
install.packages("devtools")
}::install_gitlab("libreumg/dataquier") devtools
For examples and additional documentation, please refer to our website.
dataquieR
reports can now use plotly
if installed. That means that, in the final report, you can zoom in the
figures and get information by hovering on the points, etc. To install
plotly
type:
install.packages("plotly")
To install all suggested packages, run:
prep_check_for_dataquieR_updates()
This command can also check for new beta releases of
dataquieR
from our own server, so not from
CRAN
:
prep_check_for_dataquieR_updates(beta = TRUE)
Hint If you are running
dataquieR
in an un-trusted setting, namely, inside a server
application, please consider disabling the import of R-serialization
files to prevent users from importing RData
(or
RDS
or even R
) files, that trigger code
execution on your machine, see, e.g., Ivan Krylov’s
blog for the reason:
# prevent rio from reading potentially code-containing files
options(rio.import.trust = FALSE)
If you do so, the example data won’t be loaded any more.
If you are using a version >= 2.0.0 of rio
, this will
be the default, so for running our examples, then, you’ll have to trust
our files by using e.g.
withr::with_options(list(rio.import.trust = FALSE), prep_get_data_frame("study_data"))
for loading our example study data into the data-frame cache, initially
and trusting our files loaded from
German Research Foundation (https://www.dfg.de/
)
(DFG: SCHM 2744/3–1
– initial concept and dataquieR
development, SCHM 2744/9-1
– NFDI
Task Force
COVID-19
use case application; SCHM 2744/3-4
–
concept extensions, ongoing )
European Union’s Horizon 2020 research and innovation program: euCanSHare, grant agreement No. 825903 – dataquieR refinements and implementations in the Square2 web application.
National Research Data
Infrastructure for Personal Health Data: NFDI 13/1
–
extension based on revised metadata concept, ongoing.
German National Cohort (NAKO Gesundheitsstudie) NAKO
(https://nako.de/
): BMBF
(https://www.bmbf.de/
): 01ER1301A
and
01ER1801A