Harmonise and integrate heterogeneous areal data with the R package arealDB. (November 2020) - Ehrmann, Steffen; Seppelt, Ralf; Meyer, Carsten
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. Highlights: Areal data are census, checklist, indicator, or other data linked to polygon units. 'arealDB ′ harmonises and integrates disparate areal data into a consistent database. 'arealDB ′ considers semantic differences in source data and documents data provenance. 'arealDB ′ combines various complex expert tools into one intuitive, easy-to-use tool. 'arealDB ′ promises time-savings and quality improvements to downstream applications.