From obs_bio joined to taxon, with lifeStage from life_stage.csv and the
D8 denominator as organismQuantity:
Usage
dwc_occurrence(
con,
dataset_key,
life_stage = NULL,
measurement_type = NULL,
absences = c("none", "sample_root"),
max_absences = 5e+06
)Arguments
- con
a DBI connection to the release
- dataset_key
the dataset
- life_stage
the registry from
read_life_stage_registry(), or NULL- measurement_type
the registry from
read_measurement_type(), or NULL- absences
"none"or"sample_root"- max_absences
refuse to derive more absences than this
Details
| Darwin Core | core |
occurrenceID | md5 of (sample_key, taxon_key, life_stage, measurement_type, depth_bin, ordinal) — stable across releases (obs_id is not) |
eventID | obs_bio.sample_key, or the root's sample_key for a derived absence |
scientificName / taxonID / taxonRank / lineage | taxon |
scientificNameID | the WoRMS LSID of taxon.worms_id; empty when the taxon has none |
lifeStage | life_stage.csv dwc_lifeStage, else the verbatim value where the registry gives it a life_stage_parent; a value the registry records as not a life stage goes to occurrenceRemarks |
organismQuantity / organismQuantityType | density_per_10m2, else density_per_1000m3, else value + its registry units |
occurrenceStatus | "present" where value > 0, "absent" where value = 0 |
The absence rule. See dwc_absence_rule(). absences = "none" (the default)
emits only rows the release holds. absences = "sample_root" additionally emits
one absent row for every (surveyed root sample x observed taxon/stage) pair with
no positive row — the sample_root minus positives rule. It is correct only for a
dataset whose protocol sorts every sample for its whole vocabulary, so it is never
the default, and max_absences (5,000,000) stops a large vocabulary from turning
a survey into a hundred million assertions nobody made.