Harmonise and integrate heterogeneous areal data with the R package arealDB

TL;DR

The paper introduces the R package arealDB, designed to harmonize and integrate diverse areal datasets efficiently, improving data quality and reducing effort in environmental and socioeconomic research applications.

Contribution

It presents a novel R package that streamlines the integration of heterogeneous areal data, addressing inconsistencies and facilitating metadata management.

Findings

Successfully integrated datasets from Brazil and USA on soybean harvested area.

Demonstrated workflow improves data consistency and documentation.

Potential to enhance scientific analysis and decision-making processes.

Abstract

Many relevant applications in the environmental and socioeconomic sciences use areal data, such as biodiversity checklists, agricultural statistics, or socioeconomic surveys. For applications that surpass the spatial, temporal or thematic scope of any single data source, data must be integrated from several heterogeneous sources. Inconsistent concepts, definitions, or messy data tables make this a tedious and error-prone process. To date, a dedicated tool to address these challenges is still lacking. Here, we introduce the R package arealDB that integrates heterogeneous areal data and associated geometries into a consistent database, in an easy-to-use workflow. It is useful for harmonising language and semantics of variables, relating data to geometries, and documenting metadata and provenance. We illustrate the functionality by integrating two disparate datasets (Brazil, USA) on the harvested area of soybean. arealDB promises quality-improvements to downstream scientific, monitoring, and management applications but also substantial time-savings to database collation efforts.