Package: deident 1.0.0

Robert Cook

deident: Persistent Data Anonymization Pipeline

A framework for the replicable removal of personally identifiable data (PID) in data sets. The package implements a suite of methods to suit different data types based on the suggestions of Garfinkel (2015) <doi:10.6028/NIST.IR.8053> and the ICO "Guidelines on Anonymization" (2012) <https://ico.org.uk/media/1061/anonymisation-code.pdf>.

Authors:Robert Cook [aut, cre], Md Assaduzaman [aut], Sarahjane Jones [aut]

deident_1.0.0.tar.gz
deident_1.0.0.tar.gz(r-4.5-noble)deident_1.0.0.tar.gz(r-4.4-noble)
deident_1.0.0.tgz(r-4.4-emscripten)deident_1.0.0.tgz(r-4.3-emscripten)
deident.pdf |deident.html✨
deident/json (API)
NEWS

# Install 'deident' in R:
install.packages('deident', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ShiftsWorked - Synthetic data set listing daily shift pattern for fictitious employees
  • starwars - Starwars characters

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.13 score 15 scripts 110 downloads 34 exports 60 dependencies

Last updated 6 days agofrom:2c0750f376. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 25 2024
R-4.5-linuxOKNov 25 2024

Exports::=.dataadaptive_noiseadd_bluradd_encryptadd_groupadd_numeric_bluradd_perturbadd_pseudonymizeadd_shuffleadd_ungroupapply_deidentapply_to_data_frameas_labelas_nameBaseDeidentBlurercategory_blurcreate_deidentdeidentdeident_job_from_folderDropEncrypterenquoenquosfrom_yamlGroupedShufflerlognorm_noisenew_deidentNumericBlurerPerturberPseudonymizerShufflerwhite_noise

Dependencies:askpassbitbit64clicliprcolorspacecpp11crayondplyrevaluatefansifarverfsgenericsggplot2gluegridExtragtablehighrhmsisobandknitrlabelinglatticelemonlifecyclemagrittrMASSMatrixmgcvmunsellnlmeopensslopenxlsxpillarpkgconfigplyrprettyunitsprogresspurrrR6RColorBrewerRcppreadrrlangscalesstringistringrsystibbletidyselecttzdbutf8vctrsviridisLitevroomwithrxfunyamlzip

Blur Example

Rendered fromblur_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Encrypt Example

Rendered fromencrypt_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Numeric Blur Example

Rendered fromnumeric_blur_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Perturb Example

Rendered fromperturb_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Rationale for De-identification

Rendered fromrationale.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Re-using Methods

Rendered fromreusing_methods.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Shuffle Example

Rendered fromshuffle_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

transformations

Rendered fromtransformations.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Worked Example

Rendered fromworked_example.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2024-11-19
Started: 2024-11-19

Readme and manuals

Help Manual

Help pageTopics
Function factory to apply white noise to a vector proportional to the spread of the dataadaptive_noise
De-identification via categorical aggregationadd_blur
De-identification via hash encryptionadd_encrypt
Add aggregation to pipelinesadd_group add_ungroup
De-identification via numeric aggregationadd_numeric_blur
De-identification via random noiseadd_perturb
De-identification via replacementadd_pseudonymize
De-identification via random samplingadd_shuffle
Apply a 'deident' pipelineapply_deident
Apply a 'deident' pipeline to a new data frameapply_to_data_frame
Base class for all De-identifier classesBaseDeident
Deidentifier class for applying 'blur' transformBlurer
Utility for producing 'blur'category_blur
Create a deident pipelinecreate_deident
Define a transformation pipelinedeident
Apply a pipeline to files on disk.deident_job_from_folder
R6 class for the removal of variables from a pipelineDrop
Deidentifier class for applying 'encryption' transformEncrypter
Restore a serialized deident from filefrom_yaml
GroupedShuffler class for applying 'shuffling' transform with data aggregatedGroupedShuffler
Function factory to apply log-normal noise to a vectorlognorm_noise
Group numeric data into basketsNumericBlurer
R6 class for deidentification via random noisePerturber
R6 class for deidentification via replacementPseudonymizer
Synthetic data set listing daily shift pattern for fictitious employeesShiftsWorked
Shuffler class for applying 'shuffling' transformShuffler
Starwars charactersstarwars
Function factory to apply white noise to a vectorwhite_noise