Navigate the Eratos Semantic Web

Eratos Semantic Web

Eratos' contextual engine uses a semantic web of JSON-LD Objects, known as Resources, to create a deep and rich context of information describing all datasets, operators, and workflows inside Eratos. This empowers users to access the knowledge they need, to make correct and accurate decisions when interacting with all areas of the platform.

How to Navigate Eratos

You can extract desired metadata of a given Eratos resource using the props and propfunction which is used in the following python example:

#Eratos adapter and credentials system
from eratos.creds import AccessTokenCreds
from eratos.adapter import Adapter
import pandas as pd
import pprint
from getpass import getpass

eratos_id = getpass('Enter the eratos key id:')
eratos_secret = getpass('Enter the eratos secret:')

ecreds = AccessTokenCreds(
  eratos_id,
  eratos_secret
)

eadapter = Adapter(ecreds)

#Read in Climate Dataset Resource
climate_dataset_block = eadapter.Resource(ern='ern:e-pn.io:resource:fcdi.block.vic-5.rcp85.mohc-hadgem2-cc.r1i1p1.csiro-ccam-r3355.v1.1hr.tasmax')
print('Climate dataset block metadata: Describes the Dataset block:')
pprint.pprint(climate_dataset_block.props())

print('Extracting primary')
pprint.pprint(climate_dataset_block.prop('primary'))

climate_dataset_metadata = eadapter.Resource(ern=climate_dataset_block.prop('primary'))

print('\n Climate dataset resource metadata: Describes the Dataset Resource:')
pprint.pprint(climate_dataset_metadata.props())

print('Extracting variables')
pprint.pprint(climate_dataset_metadata.prop('variables'))
print('\n Climate dataset variable (tasmax) metadata: Describes the variable Resource:')
variable_metadata = eadapter.Resource(ern=climate_dataset_metadata.prop('variables')[0]['is'])
pprint.pprint(variable_metadata.props())

print('Extracting units')
pprint.pprint(variable_metadata.prop('units'))
print('\n Climate dataset variable (tasmax) metadata: Describes the Units Resource:')
unit_metadata = eadapter.Resource(ern=variable_metadata.prop('units')[0])
pprint.pprint(unit_metadata.props())

R is supported and examples will be coming soon.

Eratos Enriches Cordex Ontology

After running the above functions you may notice some repetition in the metadata – this is not an error. Eratos wants to maintain the international cordex standards that Climate Scientists are familiar with, whilst also creating Eratos representations (resources) of these key pieces of metadata for interoperability. Eratos' approach to this is shown in the diagram below, with more detail described here. Note some climate datasets may have cordex metadata missing, however, Eratos' contextual web of metadata will always be available for all datasets.

Updated 8 days ago