README.md

In dataquieR: Data Quality in Epidemiological Research

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

Installation

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")
}
devtools::install_gitlab("libreumg/dataquier")

For examples and additional documentation, please refer to our website.

Suggested packages

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")

References

• Software Paper
• Data Quality Concept Paper
• Data Quality Concept and Software Web Site

Funding – see also here

• German Research Foundation (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: BMBF (https://www.bmbf.de/): 01ER1301A and 01ER1801A

dataquieR documentation built on May 29, 2024, 7:18 a.m.