Extra info for sorting

FROM HERE ON NEEDS SOME WEEDING TO WORK OUT WHAT MIGHT BE THE MOST USEFUL WAY TO SHOW SOME OF THESE EXAMPLES WITHOUT REPEATING EARLIER CONTENT

Region

Filter data whose site is located within a specific region.

Example 1 - Data collected in the Bioregion Cape York Peninsula

"region": [
  "http://linked.data.gov.au/dataset/bioregion/CYP"
]

Example 2 - Data collected in the Queensland state

"region": [
      "http://linked.data.gov.au/dataset/asgs2016/stateorterritory/3"
    ]

Example 3 - Data collected either in Tasmania or in Cape York Peninsula

"region": [
      "http://linked.data.gov.au/dataset/asgs2016/stateorterritory/6",
      "http://linked.data.gov.au/dataset/bioregion/CYP"
    ]

Dataset

Filter data by dataset.

Example - Data from “Tern Surveillance Monitoring” or “Williams Wet Tropics Vertebrates”

"dataset": [
  "http://linked.data.gov.au/dataset/ausplots",
  "http://linked.data.gov.au/dataset/wet-tropics-vertebrate"
]

Site

Retrieve data from 1 or more ecological monitoring sites.

Example - Retrieve all the data from Tern Surveillance Monitoring site nsabbs0001

"site_id": [
  "http://linked.data.gov.au/dataset/ausplots/site-nsabbs0001"
]

Site Visit

Retrieve data from 1 or more ecological monitoring sites.

Example - Retrieve all the data from Tern Surveillance Monitoring sitevisit 58580

"site_visit_id": [
  "http://linked.data.gov.au/dataset/ausplots/sv-58580"
]

Feature type (feature of interest)

EcoPlots observations are categorised in Feature of Interest (FOI). Please see the FOI vocabularies for more detail.

Example - Retrieve all the data from Landform feature of interest

"feature_type": [
  "http://linked.data.gov.au/def/tern-cv/2cf3ed29-440e-4a50-9bbc-5aab30df9fcd"
]

Parameter (observable property)

Each observation in EcoPlots is measuring an observable property (or parameter). Please see the Parameter vocabularies for more detail.

Example - Get all the data from Crown cover parameter.

"observed_property": [
  "http://linked.data.gov.au/def/tern-cv/83ac0278-51cd-4d1a-8e05-7c1fc68cf020"
]

Temporal extent (date)

In addition to all the vocabularised facets, you can filter data based on a temporal resolution.

"date_from": "2006-01-01",
"date_to": "2021-07-30"

Spatial extent

Need to explain how this works and how to do this.

Statial queries in EcoPlots allows three different formats: GeoJSON, Well-Known Text (WKT) and Bounding Box. The spatial query will do an “intersect” between the given geometry and the geometry of the data.

# WKT examples:
"spatial": "POINT (-77.03653 38.897676)"
"spatial": "LINESTRING (-77.03653 38.897676, -77.009051 38.889939)"
"spatial": "POLYGON ((100.0 0.0, 101.0 0.0, 101.0 1.0, 100.0 1.0, 100.0 0.0))"
"spatial": "MULTIPOINT (102.0 2.0, 103.0 2.0)"
"spatial": "MULTILINESTRING ((102.0 2.0, 103.0 2.0, 103.0 3.0, 102.0 3.0), (100.0 0.0, 101.0 0.0, 101.0 1.0, 100.0 1.0), (100.2 0.2, 100.8 0.2, 100.8 0.8, 100.2 0.8))"
"spatial": "MULTIPOLYGON (((102.0 2.0, 103.0 2.0, 103.0 3.0, 102.0 3.0, 102.0 2.0)), ((100.0 0.0, 101.0 0.0, 101.0 1.0, 100.0 1.0, 100.0 0.0), (100.2 0.2, 100.8 0.2, 100.8 0.8, 100.2 0.8, 100.2 0.2)))"

# GEOJSON examples:
"spatial": {
    "type" : "Point",
    "coordinates" : [-77.03653, 38.897676]
}

"spatial": {
    "type" : "LineString",
    "coordinates" : [[-77.03653, 38.897676], [-77.009051, 38.889939]]
}
  
"spatial": {
    "type" : "Polygon",
    "coordinates" : [
      [ [100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0] ]
    ]
}
  
"spatial": {
    "type" : "MultiPolygon",
    "coordinates" : [
      [ [[102.0, 2.0], [103.0, 2.0], [103.0, 3.0], [102.0, 3.0], [102.0, 2.0]] ],
      [ [[100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0]],
        [[100.2, 0.2], [100.8, 0.2], [100.8, 0.8], [100.2, 0.8], [100.2, 0.2]] ]
    ]
}
  
"spatial": {
    "type": "MultiPoint",
    "coordinates": [
        [
            139.213700000,
            -34.358210000
        ],
        [
            150,
            -35
        ]
    ]
}

# Bounding Box (BBOX) example
"spatial": [139.2, -34.35, 140.0, -35.00]