Publishing eDNA Data in OBIS

From sequences to a global open biodiversity record

Saara Suominen

2026-08-19

What is OBIS?

Ocean Biodiversity Information System

  • Global open-access data system for marine life
  • UNESCO Intergovernmental Oceanographic Commission
  • > 199 M occurrence records from >7,000 datasets
  • Data flows to GBIF — easy to publish once, reach both

Free to use. Free to contribute.

A Mature Global Community

OBIS is the world’s largest open-access repository
for marine biodiversity data.



36 nodes
across 99 countries
representing 1,000+ institutions
and 6,000+ scientists.

Why publish eDNA data?

eDNA captures what other methods miss

  • Cryptic and rare marine taxa
  • Non-invasive, scalable sampling
  • Community-level biodiversity signals

Shared eDNA data is powerful data

  • Data contributes to global analyses
  • Data has long-term value
  • Your sequences become findable via OBIS sequence search tools
Benefit Why it matters
Open DOI Citable in publications
Long-term archive FAIR data
Global reach OBIS + GBIF
Sequence search Reuse & reanalysis

What is special about eDNA data?

Enormous potential…

  • Expands access to biodiversity data at scale
  • Captures environmental, specimen, and bulk-sample DNA
  • Raw sequences already widely shared in NCBI

…but NCBI alone is not enough

  • Raw sequences cannot be searched by species in time and space
  • No link to spatial coordinates or sampling date
  • Cannot support distribution maps, trend analyses, or MPA assessments

What is special about eDNA data?

Special considerations

⚗️ Derived information — not a direct observation; extensive lab and bioinformatic processing

📚 Relies on reference databases — results depend on database completeness

❓ Large fraction of unknown sequences — no match in any database

📋 The DwC DNA Extension records how work was done, enabling future re-analysis

eDNA data standards

Two major eDNA data standards exist

  1. MiXS
    (Minimum Information about any (x) Sequence) — for raw sequences in NCBI
  1. Darwin Core (DwC)
    Community vocabulary for biodiversity data — species, location, date, basis of record

OBIS + GBIF + ALA accept genetic data linked to spatial coordinates and time


🔜Developing landscape

  • Rapidly changing field
  • For OBIS future directions include the DWC-DP and FAIReDNA terms

Darwin Core + DNA Derived Data Extension

  • Darwin Core: shared vocabulary for biodiversity data
  • DNA Extension: adds MIxS terms for sequences, primers, methods
  • Developed jointly by GBIF, OBIS, and the genomics community

meta.xml ← links all tables
eml.xml ← metadata (who, what, where, when, how)
occurrence.csv ← the occurrence records
dna_derived.csv ← the DNA extension

The DNA publishing guide

Publishing DNA-derived data through biodiversity data platforms

Five DNA data categories

Which one fits your data?

# Category Example
1 DNA-derived occurrences Metabarcoding (ASVs/OTUs assigned to taxa)
2 Enriched occurrences Voucher specimen + barcoded
3 Targeted species detection qPCR / ddPCR assays
4 Name references Sequence in GenBank only
5 Metadata only Dataset without sequences

🔎 Use the GBIF decision tree to confirm your category

From raw outputs → long format

DNA data is more complex than a lat/lon + species name

Your typical metabarcoding outputs:

File Content
OTU/ASV table Sequences × Samples (read counts)
Taxonomy table Sequence [ID] → taxon assignment
Sample metadata Location, date, method
FASTA file Actual DNA sequences

The transformation:

One row = one unique sequence in one sample = one occurrence record

Example transformation

Key DwC fields to include: Occurrence

Occurrence (core) table (mandatory fields)

  • occurrenceIDunique, stable ID
  • scientificNametaxon name to lowest possible taxon rank
  • basisOfRecord = “MaterialSample”
  • occurrenceStatus = “present”

If Occurrence core, also: eventDate, decimalLatitude, decimalLongitude

Occurrence table (strongly recommended fields)

  • scientificNameID (WoRMS AphiaID)
  • organismQuantity (read count of sequence)
  • organismQuantityType = “DNA sequence reads”
  • sampleSizeValue (total read count in sample)
  • sampleSizeUnit = “DNA sequence reads”
  • samplingProtocol - (link to your SOP)
  • associatedSequences (link to e.g. GenBank or ENA accession)

WoRMS Taxon Matching

Options for taxon matching:

No WoRMS match?

Use highest-rank taxon with a match (e.g. family or order). Keep the sequence — it can be re-identified later as reference databases improve.

Still no match?

Unknown sequences recorded as: scientificName = “Biota incertae sedis” scientificNameID = urn:lsid:marinespecies.org:taxname:12

Key fields to include: DNA Extension

DNA Extension (example key fields)

  • DNA_sequenceASV/OTU sequence
  • target_genee.g. “COI”, “18S rRNA”
  • pcr_primer_name_forwardand reverse
  • seq_methe.g. “Illumina MiSeq”
  • otu_class_appre.g. “DADA2 v1.18”
  • otu_dbreference database
  • soplink to your protocol

Table structure options

Option A — Occurrence Core

occurrence.csv 
  └── dna_derived.csv  (linked via occurrenceID)
  └── emof.csv         (linked via occurrenceID)

Option B — Event Core (recommended for eDNA)

event.csv
  └── occurrence.csv        (linked via eventID)
       └── dna_derived.csv  (linked via occurrenceID)
  └── emof.csv              (linked via eventID or occurrenceID)

Why Event Core? Sample-level metadata (location, date, method) is recorded once per sampling event rather than repeated in every row.

Dataset Structure: Three Linked Tables

Event Core

  • eventID
  • eventDate
  • decimalLatitude
  • decimalLongitude
  • samplingProtocol

→ the 📍where, 🕒when & 🧪how of collection

Occurrence Extension

  • occurrenceID
  • eventID
  • scientificName
  • taxonID (WoRMS)
  • basisOfRecord
  • occurrenceStatus

→ what organism was detected 🐠🪸🪼

DNA Derived Data Ext.

  • occurrenceID
  • DNA_sequence
  • target_gene
  • pcr_primer_forward
  • pcr_primer_reverse
  • seq_meth

→ 🧬the molecular context


Tables linked by eventID and occurrenceID

Optional 4th table: eMoF for measurements and facts

Example usage of Event core structure

  • Why Event Core? Sample-level metadata (location, date, method) is recorded once per sampling event rather than repeated in every row.

eMoF extension table

  • Table to record all types of measurements (abiotic, biotic, environmental, sampling…)
  • Measurements recorded in long format
    • measurementType, measurementValue, measurementUnit
  • Linking sampling info to eventIDs decreases duplication
  • Use controlled vocabulary whenever possible!
eventID occurrenceID measurementType measurementValue measurementUnit
YEARsite1samp1 temperature 25 C
measurementTypeID measurementUnitID
http://vocab.nerc.ac.uk/collection/P01/current/TEMPPR01/ http://vocab.nerc.ac.uk/collection/P06/current/UPAA/

Controlled Vocabulary

Identifiers for each eMoF column

  • measurementUnitID
  • measurementValueID
    • non-numeric values
  • measurementTypeID

→ Facilitates data understanding

→ Enables data aggregation

→ Decreases misuse potential

What should vocabulary terms capture?

OBIS recommends using NERC vocabulary terms

Publishing workflow

Integrated Publishing Toolkits (IPT) are hosted by OBIS nodes — you do not need to run your own server. OBIS has nodes covering most world regions. Find yours at obis.org/nodes.

Tools to Help You

GBIF Metabarcoding Data Toolkit

Automates DwC mapping from bioinformatic outputs

gbif.org/tools/mdt

robis (R package)

Query OBIS; retrieve DNA records with unnest_extension()

github.com/iobis/robis

obistools (R package)

Validation, QC, WoRMS matching, archive structure checks

github.com/iobis/obistools

OBIS Sequence Search

BLAST-search sequences already in OBIS (prototype)

sequence.obis.org

The Metabarcoding Data Toolkit (MDT)

A newer tool to simplify the workflow

  • Developed by GBIF specifically for metabarcoding data
  • Accepts common pipeline outputs (QIIME2, DADA2, etc.)
  • Handles the wide-to-long transformation
  • Generates Darwin Core Archive + DNA Extension automatically
  • Integrates with IPT publishing

🔗 Available at: mdt.gbif.org

Note

Still under active development — check the GBIF documentation for the latest capabilities. Currently not possible to use the event core structure

Quality control

Before publishing — check for:

  • ✅ Taxonomy matched to WoRMS (AphiaID required for marine taxa)
  • ✅ Coordinates in decimal degrees, in the ocean
  • ✅ Dates in ISO 8601 format (YYYY-MM-DD)
  • ✅ Unique, stable occurrenceID and eventID
  • ✅ Table linkages consistent (eventID, occurrenceID)

Tools:

Tool What it checks
obistools (R package) Taxonomy, geography, required fields
GBIF data validator Darwin Core Archive structure
WoRMS taxon match Scientific names → AphiaIDs

Resources and community

Resource Link
OBIS Manual (DNA chapter) manual.obis.org/dna_data.html
OBIS DNA training slides (this presentation!) github.com/iobis/obis_edna_slides
GBIF DNA publishing guide doi.org/10.35035/DOC-VF1A-NR22
OBON 2024 DNA training github.com/iobis/obon-2024-dna-training
IOOS Bio Mobilization Workshop ioos.github.io/bio_mobilization_workshop
GBIF-NA DNA Publishing Workshop sunray1.github.io/2025-05-09-GBIF-NA-DNAPublishing
OBIS helpdesk helpdesk@obis.org

OBIS DNA Data Management Platform

🔧 OBIS is developing a data management platform for DNA data including:

  • Bioinformatics
  • QC
  • Validation
  • Publication to OBIS pipeline

To be offered to OBIS nodes to support local eDNA projects!

🚧

Summary

Three steps to publish your eDNA data:

  1. Format — Darwin Core + DNA Derived Data Extension
    Long format: one row = one sequence per sample

  2. Document — Complete EML metadata
    Primers, methods, bioinformatics pipeline, license

  3. Publish — Through your OBIS node IPT
    Get a DOI. Be cited. Join the global record.


Start here → manual.obis.org/dna_data.html

Why it matters

eDNA captures biodiversity no other method can.
Publishing it in OBIS makes it
reusable, citable, and permanent.