datacleanr

datacleanr performs interactive data cleaning and generates reproducible R code to support quality control and exploration of time series, georeferenced, and hierarchically nested tabular datasets for ecological and Earth System Science analyses.

Key Features:

• Interactive Data Processing: Provides interactive computational processing of datasets to inspect and modify records during analysis.
• Reproducibility (reproducible recipe): Translates all interactive actions into R code to preserve reproducible processing steps for integration into script-based workflows.
• Quality Control and Data Exploration: Supports outlier assessment and quality-control practices for multiple tabular data types, including time series and georeferenced data.
• Flexibility Across Data Types: Handles diverse tabular structures and formats common in ecological and Earth System Sciences analyses.
• Handling Complex Data Issues: Identifies problematic structures and artifacts in hierarchically nested data and aims to avoid excessive data loss from coarse, code-based filtering of time series.

Scientific Applications:

• Ecological research: Cleaning and quality-controlling ecological datasets including time series and georeferenced observations.
• Earth System Sciences: Processing complex, multiscale tabular data used in Earth System Science studies.
• Reproducible R workflows: Integrating interactive cleaning steps into reproducible R analysis pipelines.

Methodology:

Interactive actions are recorded and translated into R code via a "reproducible recipe"; methods explicitly include interactive data processing, outlier assessment, handling of time series and georeferenced tabular data, identification of artifacts in hierarchically nested data, and measures to prevent excessive data loss from coarse code-based filtering of time series.