R Observatory: Metrics for dataquieR version 2.8.15

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

dataquieR

2.8.15Package record

Data Quality in Epidemiological Research

0packages depend

9.2Kdownloads / year

–test coverage

11/13flavors OK

Overview

About

Maintained by Stephan StruckmannCRAN page ↗GitLab ↗Website ↗Issues ↗Declared funders: European Union’s Horizon 2020 programme (euCanSHare, grant agreement No. 825903), German Federal Ministry of Education and Research (BMBF; NAKO Gesundheitsstudie, grants 01ER1301A and 01ER1801A) and 2 more

Data quality assessments guided by a 'data quality framework introduced by Schmidt and colleagues, 2021' doi:10.1186/s12874-021-01252-7 target the data quality dimensions integrity, completeness, consistency, and accuracy. The scope of applicable functions rests on the availability of extensive metadata which can be provided in spreadsheet tables. Either standardized (e.g. as 'html5' reports) or individually tailored reports can be generated. For an introduction into the specification of corresponding metadata, please refer to the 'package website' https://dataquality.qihs.uni-greifswald.de/VIN_Annotation_of_Metadata.html.

Changes in 2.8.15

HTML report tables now keep numeric descriptive statistics aligned with their variables when some results are empty.
Summary pie charts now display percentages consistently with one decimal place in both ggplot2 and Plotly output.
HTML report tables now keep their column headers visible while scrolling and recalculate column widths after responsive resizing with both the DT and DT2 backends. Metadata tables again reveal and hide automatically generated variables even when the displayed label differs from the variable name.
Fixed automatic study-data discovery in dq_report_by() so dataframe-level metadata remain separate from study records. This restores dataframe-level integrity results and prevents study records from appearing on metadata report pages. Overview calls no longer claim that study_data was supplied when it was discovered from dataframe-level metadata, preserve the distinction between omitted and explicitly empty response-variable selections, and correctly filter item-computation metadata for selected response variables.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("dataquieR", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("libreumg/dataquier")

Development version from libreumg/dataquier. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-dataquier

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-dataquieR

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-dataquieR

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

2NOTE11OK

Check messages

NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Maintainer: ‘Stephan Struckmann <stephan.struckmann@uni-greifswald.de>’

The BugReports field in DESCRIPTION has
  https://gitlab.com/libreumg/dataquier/-/work_items
which should likely be
  https://gitlab.com/libreumg/dataquier/-/issues
instead.

CRAN check page ↗

Slowest check: 14.1 min · r-oldrel-windows-x86_64

Status changes

NOTE11 OK, 2 NOTE2026-09-24
ERROR7 OK, 5 NOTE, 1 ERROR2026-09-11
NOTE10 OK, 3 NOTE2026-07-16
OK13 OK2026-07-10
ERROR12 OK, 1 ERROR2026-07-04

Show 15 earlier changesHide 15 earlier changes

OK13 OK2026-07-03
ERROR12 OK, 1 ERROR2026-06-27
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK13 OK2026-06-06
ERROR12 OK, 1 ERROR2026-06-04
OK13 OK2026-05-15
ERROR11 OK, 2 ERROR2026-05-12
OK13 OK2026-05-07
ERROR12 OK, 1 ERROR2026-04-30
OK13 OK2026-04-28
ERROR13 OK, 1 ERROR2026-04-23
OK14 OK2026-04-22
ERROR13 OK, 1 ERROR2026-04-18
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 2.8.15

READMEYes · 780 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 2.8.15Citation fileYes · cites a publicationWebsiteYes

Cites a JOSS paper

Help pages: 350 (16 internal)includes a package overview page
Examples that run: 3%1 run in a plain check · 31 never run
Exported functions with examples: 17%
Documented parameters: 93%
Return-value docs: 68%
Help pages citing references: 0%

Vignettes (1)

dataquieR HTML

How these are measured

Downloads

9.2K

CRAN downloads in the past year

Rank #4,306 · ~25/day · ~767/mo

Releases R versions

Daily download trend is not available in this view yet.

96830 days

2K90 days

9.2K1 year

Compare downloads with other packages →

Also on218 r2u22 autocran

How downloads are counted

Repository

gitlab.com/libreumg/dataquier ↗

7Stars

5Forks

198Open issues

0Open PRs

72Releases

data quality

Last activity 2026-09-27

Responsiveness

How these are sampled

PRs merged (all time): 33%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: not measured

How these are measured

PracticesBeta

Repository gitlab.com/libreumg/dataquier is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

58 external dependencies (excludes base and recommended)

Installing dataquieR adds 68 packages (36 with compiled code, 50 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, lme4 4.1 MB.

Depends (1)

R >= 4.1.0

Imports (22)

dplyr emmeans ggplot2 lme4 lubridate patchwork rlang robustbaseutilsrio readr scales withr lifecyclemethodsmgcvnnetgridgrDevicesparallelhtmltools hms

LinkingTo (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (12)

Stephan Struckmann

Author, Maintainer since 1.0.3 (2021)

Elisa Kasbohm

Author · added in 1.0.11

Joany Marino

Author · added in 1.0.11

Elias Peschke

Author · added in 2.8.15

Adrian Richter

Author

Elena Salogni

Author · added in 2.1.0

Carsten Oliver Schmidt

Author

University Medicine Greifswald

Copyright holder · added in 1.0.5

European Union’s Horizon 2020 programme (euCanSHare, grant agreement No. 825903)

Funder · added in 1.0.11

German Federal Ministry of Education and Research (BMBF; NAKO Gesundheitsstudie, grants 01ER1301A and 01ER1801A)

Funder · added in 2.8.15

German Research Foundation (DFG SCHM 2744/3-1, SCHM 2744/9-1, SCHM 2744/3-4)

Funder · added in 2.0.0

National Research Data Infrastructure for Personal Health Data: (NFDI 13/1)

Funder · added in 2.0.0

Listed in earlier versions (1)

German Research Foundation (DFG SCHM 2744/3-1)

no longer listed · 1.0.11 to 1.0.13

Releases (18)

Pick two releases to compare their code metrics.

2.8.15Latest
record
2026-09-22 · current release · diff ↗ ·
removed 2 exports
GOLDSTANDARD, REL_VAL

added 12 exports
REPEATED_MEASURES_METRIC, REPEATED_MEASURES_METRIC_SETTING, REPEATED_MEASURES_REFERENCE, acc_repeated_measurements, con_attention_check_items, con_schema_nonadherence, con_ssi_range_check, dq_questionnaire, dq_shiny_panel_html, dq_shiny_panel_server, dq_shiny_panel_ui, int_invalid_syntax
2.8.9
record
2026-05-11 · diff ↗ ·
added 6 exports
MISSING_CODE_RULES, acc_mahalanobis_ratio, prep_deregister_progress_hook, prep_is_translated, prep_register_progress_hook, to_basic.GeomPointrangeRobust
R
R 4.6.0 released · 2026-04-24
2.8.7
record
2026-01-08 · diff ↗ ·
added 2 exports
dataquieR.applicability_problem, dataquieR.intrinsic_applicability_problem
2.8.2
record
2025-12-23 · diff ↗ ·
removed 2 exports
N_RULES, UNIVARIATE_OUTLIER_CHECKTYPE

added 16 exports
COMPUTATION_RULE, MAHALANOBIS_THRESHOLD, SCALE_ACRONYM, SCALE_NAME, VARIABLE_LIST_ORDER, acc_mahalanobis, dataquieR.study_data_cache_metrics_env_default, ggplotGrob.dq_lazy_ggplot, ggplotGrob.dq_lazy_ggplot_s7, ggplotly.dq_lazy_ggplot, ggplotly.dq_lazy_ggplot_s7, html_dependency_jspdf, plotly_build.dq_lazy_ggplot, plotly_build.dq_lazy_ggplot_s7, prep_fix_meta_id_dups, prep_realize_ggplot
R
R 4.5.0 released · 2025-04-11
2.5.1
record
2025-03-05 · diff ↗
2.5.0
record
2025-02-20 · diff ↗ ·
removed 2 exports
acc_distributions_loc_ecdf, acc_distributions_only_ecdf

added 32 exports
CODE_CLASS, CODE_CLASSES, CODE_INTERPRET, CODE_LABEL, CODE_LIST_TABLE, CODE_ORDER, CODE_VALUE, DF_CODE, MULTIVARIATE_OUTLIER_CHECK, RULE, SEGMENT_UNIQUE_ID, acc_cat_distributions, acc_distributions_ecdf, con_inadmissible_vocabulary, des_summary_categorical, des_summary_continuous, int_encoding_errors, prep_acc_distributions_with_ecdf, prep_add_computed_variables, prep_compare_meta_with_study, prep_create_storr_factory, prep_get_study_data_segment, prep_get_variant, prep_guess_encoding, prep_list_voc, prep_load_report_from_backend, prep_open_in_excel, prep_remove_from_cache, prep_robust_guess_data_type, prep_set_backend and 2 more
R
R 4.4.0 released · 2024-04-24
2.1.0
record
2024-03-29 · diff ↗ ·
removed 3 exports
con_detection_limits, con_hard_limits, con_soft_limits

added 14 exports
SCALE_LEVELS, SEGMENT_ID_REF_TABLE, des_scatterplot_matrix, des_summary, prep_combine_report_summaries, prep_create_meta_data_file, prep_extract_classes_by_functions, prep_extract_summary, prep_get_labels, prep_load_folder_with_metadata, prep_render_pie_chart_from_summaryclasses_ggplot2, prep_render_pie_chart_from_summaryclasses_plotly, prep_scalelevel_from_data_and_metadata, prep_summary_to_classes
2.0.1
record
2023-07-19 · diff ↗ ·
removed 1 export
acc_distributions_prop_ecdf

added 23 exports
.get_internal_api, API_VERSION, ASSOCIATION_DIRECTION, ASSOCIATION_FORM, ASSOCIATION_METRIC, ASSOCIATION_RANGE, CHECK_ID, CHECK_LABEL, CONTRADICTION_TERM, CONTRADICTION_TYPE, DATA_PREPARATION, GOLDSTANDARD, MULTIVARIATE_OUTLIER_CHECKTYPE, N_RULES, REL_VAL, SEGMENT_MISS, UNIVARIATE_OUTLIER_CHECKTYPE, VARIABLE_LIST, acc_distributions_only, acc_distributions_only_ecdf, prep_check_for_dataquieR_updates, prep_load_report, prep_save_report
R
R 4.3.0 released · 2023-04-21
2.0.0
record
2023-03-01 · diff ↗ ·
added 56 exports
DF_ELEMENT_COUNT, DF_ID_REF_TABLE, DF_ID_VARS, DF_NAME, DF_RECORD_CHECK, DF_RECORD_COUNT, DF_UNIQUE_ID, DF_UNIQUE_ROWS, SEGMENT_ID_TABLE, SEGMENT_ID_VARS, SEGMENT_PART_VARS, SEGMENT_RECORD_CHECK, SEGMENT_RECORD_COUNT, SEGMENT_UNIQUE_ROWS, acc_distributions_loc, acc_distributions_loc_ecdf, acc_distributions_prop, acc_distributions_prop_ecdf, com_qualified_item_missingness, com_qualified_segment_missingness, con_contradictions_redcap, con_hard_limits, con_soft_limits, dq_report2, int_all_datastructure_dataframe, int_all_datastructure_segment, int_duplicate_content, int_duplicate_ids, int_part_vars_structure, int_sts_element_dataframe and 26 more
1.0.13
record
2022-11-16 · diff ↗
1.0.12
record
2022-11-11 · diff ↗
1.0.11
record
2022-10-11 · diff ↗

Show 9 earlier eventsHide 9 earlier events

1.0.10
record
2022-08-31 · diff ↗
R
R 4.2.0 released · 2022-04-22
1.0.9
record
2021-09-03 · diff ↗
1.0.8
record
2021-08-12 · diff ↗ ·
added 2 exports
int_datatype_matrix, prep_valuelabels_from_data
R
R 4.1.0 released · 2021-05-18
1.0.5
record
2021-02-26 · diff ↗
1.0.4
record
2021-02-02 · diff ↗
1.0.3
record
2021-01-26
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2021-01-26
Total releases: 18 / 5 yrs
License: BSD_2_clause + file LICENSE OSI · relicensed from CC BY 4.0 in 1.0.5
Minimum R: ≥ 4.1.0
Download size: 3.2 MB

Appears in task views

Epidemiology

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("dataquieR")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for dataquieR version 2.8.15 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →