The data was obtained from ALA. Here is the DOI to the data.
This repository contains a worked example of converting ALA data from Darwin Core to the TERN Ontology.
A mapping spreadsheet of the data to the RDF terms in the TERN Ontology.
The source data downloaded from ALA is the records-2021-12-01.csv file.
A mapping spreadsheet was created to map the columns of the CSV file to the TERN Ontology.
The run.py script is used to convert the CSV file to RDF.
View the data in Ontodia at https://ternaustralia.github.io/bdr-faealla-worked-example.
The worked example was created based on the following assumptions:
- Each row in the CSV file represents a Darwin Core record. These records are represented in the TERN Ontology with the class
tern:RDFDataset. - All items in a row (observation, sampling, etc.) are part of an
tern:RDFDatasetinstance. - The provenance and country code information are recorded in the
tern:RDFDatasetclass astern:Attributeinstances. - Sites are inferred from the location remarks and the decimal latitude and longitude values.
- Occurrences are recorded with the class
tern:Sampling. The sampling events take place from within the established site. The result of the sampling is an occurrence recorded as atern:Sample. - The person who performed the samplings and observations also established the site.
- Three possible observations are made on the occurrence (fauna) sample:
- sex (gender) of the occurrence
- life stage of the occurrence
- habitat description of the occurrence
- A specimen of an occurrence is recorded with the class
tern:MaterialSample. The way the specimen was collected are recorded with the classtern:Sampling. - Two possible observations are made on the specimen:
- type status
- taxonomic information (captured with the
tern:Taxon)
- Attribution to people are recorded with the property
prov:wasAssociatedWith.
TERN Support esupport@tern.org.au