AURORA - A Shiny app designed to create Darwin Core Archives from messy biodiversity datasets

What this was about

Sara Araújo presents the AURORA Shiny app, a browser-based R Shiny workflow of eight steps that turns non-standard occurrence tables into Darwin Core tables ready for publication. It supports tidying, header-to-term mapping with suggestions, creating ID and dependent fields, repository-specific required-term validation (OBIS, GBIF, EMODnet Biology), date and coordinate conversion, taxonomic cleaning and matching against WoRMS or the GBIF backbone, event/occurrence restructuring, eMoF creation, quality control and IPT-style metadata. It does not build the archive itself (the IPT does) and currently supports only a limited set of cores and extensions.

Why it matters. Standardization is a main barrier to data publication; a free, guided tool can bring more datasets into GBIF, OBIS and EMODnet.

In the room

• Eight-step workflow: upload/tidy, map headers to Darwin Core terms, create key fields, validate required terms, transform dates and coordinates, clean and match taxonomy, structure event core/occurrence/eMoF, quality control and metadata export.
• Required terms adapt to the target repository (OBIS, GBIF, EMODnet Biology).
• Taxonomic validation via WoRMS (marine) or GBIF backbone (terrestrial) retrieves scientificNameID and taxonRank.
• eMoF measurements are assigned to events (e.g. temperature) or occurrences (e.g. life stage) and can use controlled vocabularies.
• Quality control produces logs, summaries and issue flags.
• Limitations: does not create the DwC-A (use the GBIF IPT); only event core + occurrence + eMoF or occurrence core + eMoF; users must know their data and basic Darwin Core.
• Funded by the EU via the DTO-BioFlow project; user manual, video tutorial and source code on GitHub.

Notable moments