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The publication workflow from the German Federation for Biological Data (GFBio) Data Centers at Natural History Collections to GBIF is relying on the BioCASe Provider Software and the ABCD standard. This approach emerged because the classical Darwin Core Archive (DwC-A) model was often insufficient for representing complex relationships between collection objects, identifications, multimedia, agents, and related entities. However, the DWB–ABCD publication pathway also revealed some limitations within the GBIF ingestion workflow, as important dataset metadata, including multiple global identifiers, associated persons, institutions, and their roles, could not always be fully represented or displayed on the GBIF portal.The Darwin Core Data Package (DwC-DP), currently evolving within the GBIF and TDWG communities, aims to combine the strengths of both approaches. Aligned with the Darwin Core Conceptual Model and new ABCD versions, DwC-DP introduces a more flexible and semantically explicit framework for biodiversity data publishing.This contribution presents a practical, AI-assisted mapping approach from DWB-based collection management software model to the emerging DwC-DP model. During the mapping process, information distributed across different DWB database modules is consolidated into DwC-DP entities while respecting existing relations, withhold settings and publication restrictions. Using real-world datasets from GFBio Data Center SNSB IT Center, we analyze how relational structures, identifiers, artefacts, material storage, agents and general metadata can be transformed into DwC-DP entities and properties.The results demonstrate the potential of DwC-DP for richer biodiversity data integration and improved metadata visibility within GBIF publishing workflows.
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Weibulat et al. (2026) studied this question.
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