Descriptron-GBIF Annotator: A browser-based platform for crowdsourced morphological annotation of biodiversity images to help accelerate morphology based biodiversity data

Abstract

The accelerating biodiversity crisis demands new approaches to taxonomic description that can scale beyond the capacity of professional taxonomists alone. We present the Descriptron-GBIF Annotator, a zero-installation, browser-based tool for morphological annotation of biodiversity specimen images retrieved directly from the Global Biodiversity Information Facility (GBIF). The application runs entirely client-side as a single HTML file, integrating SAM2 (Segment Anything Model 2) for AI-assisted segmentation, ontology-linked anatomical region templates covering 25 major taxonomic groups across 124 standardized views, 335 ontology Compact URI Expressions (CURIEs), with 745 possible ontology mentions, and structured trait attribute recording. The annotator supports multiple export formats including Darwin Core JSON, COCO JSON, traits CSV, and a novel JSON-LD knowledge graph linking specimens to anatomical regions and morphological traits via UBERON and domain-specific ontologies. A built-in Zenodo publishing pipeline enables users to deposit annotations as citable datasets with DOIs directly from the browser. Additionally users can also annotate images from Zenodo BioSysLit enabling annotation of taxonomic treatments directly. We position this public-facing tool as the first tier of a two-tier architecture complementing the Descriptron Portal, a GPU-accelerated professional workbench for taxonomists providing tools for fine-tuning AI models, geometric morphometrics, and automated species descriptions. Together, these tiers create a feedback loop where public annotations generate training data for expert AI models, while expert-validated outputs improve the public tool. This approach draws on the citizen science model pioneered by Notes from Nature and iNaturalist to engage diverse audiences in structured morphological data collection, addressing a critical gap in biodiversity informatics where specimen images exist in abundance but structured morphological annotations remain scarce. To learn more go here: https://descriptrongbifannotator.org