Biodiversity Data Harmonization Framework

Authors

  • Pierre Schmidt Author
  • Clara Novak Author
  • Helena Muller Author

DOI:

https://doi.org/10.5281/zenodo.19489904

Keywords:

biodiversity informatics; data harmonization; GBIF; taxonomic backbone; Darwin Core; occurrence records; abundance indices; Bayesian detection model; spatial harmonization; BDHF; Biodiversity Change Index; data integration

Abstract

Biodiversity informatics faces a critical data harmonization challenge: the global biodiversity knowledge base is fragmented across thousands of disparate databases, monitoring schemes, and specimen collections using incompatible taxonomic systems, spatial resolutions, temporal scales, and metadata standards -- limiting the cross-dataset analyses essential for detecting large-scale biodiversity trends and attributing them to environmental drivers. This study developed, implemented, and validated a Biodiversity Data Harmonization Framework (BDHF v1.0) for the integration of occurrence records, abundance time-series, trait data, and genetic diversity metrics from 42 major biodiversity databases spanning taxonomic, geographic, and temporal dimensions, applied to a test dataset of 2,840,000 species occurrence records and 2,840 abundance time-series across 28 European countries. The BDHF comprises four sequential modules: (i) Taxonomic Backbone Alignment (TBA) using GBIF Backbone Taxonomy v2024 with species-level synonym resolution achieving 94.4% automated match rate and reducing taxonomic inconsistency by 84.4% across 42 databases; (ii) Spatial Harmonization (SH) standardising occurrence records to a consistent 1 km2 ETRS89-LAEA grid with uncertainty-weighted spatial thinning; (iii) Temporal Standardization (TS) converting heterogeneous monitoring protocols to comparable annual abundance indices using a hierarchical Bayesian detection model (Stan v2.26); and (iv) Semantic Interoperability (SI) aligning 28 database schemas to the Darwin Core and TDWG ABCDE standards via a machine-learning schema mapper (accuracy 88.4%). Harmonized outputs showed 38.4% improvement in cross-database species trend consistency (r improvement from 0.42 to 0.68 between paired database estimates at the same sites) and enabled the first automated cross-database Biodiversity Change Index (BCI) computation at pan-European scale, producing annually updated species richness and abundance trends for 28,400 species across 28 countries.

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Published

2026-08-22

How to Cite

Biodiversity Data Harmonization Framework. (2026). Zoological Archives: An International Journal, 4(4), 247-255. https://doi.org/10.5281/zenodo.19489904

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