This Python script aggregates biologging (machine) observations as a demonstration of a possible way to summarize such data before supplying it to GBIF.
The dataset used is the example from the TDWG dwc-for-biologging group, it's description from there is:
This dataset is a subset of GPS and acceleration data from collared mammals described in Mahoney and Young (2016) Uncovering behavioural states from animal activity and site fidelity patterns. Methods in Ecology and Evolution 8(2): 174–183. The data are stored on Movebank in the study "Site fidelity in cougars and coyotes, Utah/Idaho USA (data from Mahoney et al. 2016)" and have been published in the Movebank Data Repository with DOI 10.5441/001/1.7d8301h2.
- (Optional) Set up a Python virtual environment, so you can throw all this away later:
python3 -m venv cougars
source cougars/bin/activate
- Install necessary Python modules
pip install -r requirements.txt
- Run the script:
python summarize.py
- Zip the result:
zip mahoney.zip meta.xml eml-Mahoney-data-DwC-A.xml event.txt occurrence.txt extendedmeasurementorfact.txt
- Send to GBIF!
The dataset is registered on GBIF's test environment as Cougar and coyote GPS telemetry, Utah/Idaho USA (OBIS-ENV-DATA example) (the test environment is reset occasionally, so the dataset may disappear).