Open digital curation can be a continuous, inclusive process that explicitly incorporates annotations, enhancements, and round-tripping across the biodiversity data lifecycle. This issue aims to illustrate how human and AI-assisted annotations—such as annotated links, incorporation of persistent unique identifiers, taxonomic determinations, trait assertions, georeferencing improvements, image and specimen labeling, and genomic metadata enrichment—can be made transparent, attributable, versioned, and reusable. Particular attention will be paid to round-tripping: annotations and AI-generated enhancements that flow back to source systems (e.g., collection management systems and institutional repositories).

With an emphasis on natural history data from museums and herbaria, the special issue may feature case studies, technical methods, and synthesis papers that bridge institutional practice, community engagement, and open science infrastructure. Contributions may address challenges such as scaling AI-enabled curation, validating and crediting annotations, aligning with standards like Darwin Core and related vocabularies, and designing workflows and user interfaces that support equitable participation by collection staff, researchers, and external contributors.