Data Validation Infrastructure for R

Data Validation Infrastructure for R

data checking, data quality, data cleaning, R

Checking data quality against domain knowledge is a common activity that pervades
statistical analysis from raw data to output. The R package validate facilitates this
task by capturing and applying expert knowledge in the form of validation rules: logical
restrictions on variables, records, or data sets that should be satisfied before they are
considered valid input for further analysis. In the validate package, validation rules are
objects of computation that can be manipulated, investigated, and confronted with data
or versions of a data set. The results of a confrontation are then available for further
investigation, summarization or visualization. Validation rules can also be endowed with
metadata and documentation and they may be stored or retrieved from external sources
such as text files or tabular formats. This data validation infrastructure thus allows for
systematic, user-defined definition of data quality requirements that can be reused for
various versions of a data set or by data correction algorithms that are parameterized by
validation rules.

Mark P. J. van der Loo

https://www.jstatsoft.org/article/view/v097i10

Mark P. J. van der Loo, Edwin de Jonge

Januari 2021

Fajar Bagus w

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