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Collection Schema #2

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Jul 26, 2021
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Collection Schema #2

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f6abfab
Hopefully better schema for collections
m-mohr Apr 23, 2021
855c1c6
Improve schema, update examples to STAC 1.0.0
m-mohr Jul 26, 2021
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7 changes: 5 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -25,8 +25,11 @@ As these citation information are often closely bound to the Collection level an
it is recommended adding the fields to the corresponding Collection.

- Examples:
- [Item](examples/item.json): Shows the usage of the extension in a STAC Item
- [Collection](examples/collection.json): Shows the usage of the extension in a STAC Collection
- [Item](examples/item.json): The extension in a STAC Item
- [Collection](examples/collection.json): The extension in a STAC Collection
- [Collection (Assets)](examples/collection-assets.json): The extension in a STAC Collection with assets
- [Collection (Item Asset Definition)](examples/collection-item-assets.json): The extension in a STAC Collection in Item Asset Defintions
- [Collection (Summaries)](examples/collection-summaries.json): The extension in a STAC Collection in Summaries
- [JSON Schema](json-schema/schema.json)
- [Changelog](./CHANGELOG.md)

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62 changes: 62 additions & 0 deletions examples/collection-assets.json
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@@ -0,0 +1,62 @@
{
"stac_version": "1.0.0-rc.1",
"stac_extensions": [
"https://stac-extensions.github.io/scientific/v1.0.0/schema.json"
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],
"id": "MERRAclim",
"title": "MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling.",
"description": "Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.",
"type": "Collection",
"keywords": [
"bioclimatic",
"MERRAclim",
"macroecology",
"biogeography"
],
"license": "CC0-1.0",
"extent": {
"spatial": {
"bbox": [
[
-180,
-90,
180,
90
]
]
},
"temporal": {
"interval": [
[
"1980-01-01T00:00:00Z",
"2009-12-31T23:59:59Z"
]
]
}
},
"assets": {
"test": {
"href": "example.xml",
"type": "application/xml",
"sci:doi": "10.5061/dryad.s2v81.2"
}
},
"links": [
{
"rel": "self",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "item",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/item.json"
},
{
"rel": "root",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "cite-as",
"href": "https://doi.org/10.5061/dryad.s2v81.2"
}
]
}
62 changes: 62 additions & 0 deletions examples/collection-item-assets.json
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@@ -0,0 +1,62 @@
{
"stac_version": "1.0.0-rc.1",
"stac_extensions": [
"https://stac-extensions.github.io/scientific/v1.0.0/schema.json"
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],
"id": "MERRAclim",
"title": "MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling.",
"description": "Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.",
"type": "Collection",
"keywords": [
"bioclimatic",
"MERRAclim",
"macroecology",
"biogeography"
],
"license": "CC0-1.0",
"extent": {
"spatial": {
"bbox": [
[
-180,
-90,
180,
90
]
]
},
"temporal": {
"interval": [
[
"1980-01-01T00:00:00Z",
"2009-12-31T23:59:59Z"
]
]
}
},
"item_assets": {
"primary": {
"type": "application/zip",
"title": "MERRAclim. 2_5m_min_80s",
"sci:doi": "10.5061/dryad.s2v81.2"
}
},
"links": [
{
"rel": "self",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "item",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/item.json"
},
{
"rel": "root",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "cite-as",
"href": "https://doi.org/10.5061/dryad.s2v81.2"
}
]
}
70 changes: 70 additions & 0 deletions examples/collection-summaries.json
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@@ -0,0 +1,70 @@
{
"stac_version": "1.0.0-rc.1",
"stac_extensions": [
"https://stac-extensions.github.io/scientific/v1.0.0/schema.json"
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],
"id": "MERRAclim",
"title": "MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling.",
"description": "Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.",
"type": "Collection",
"keywords": [
"bioclimatic",
"MERRAclim",
"macroecology",
"biogeography"
],
"license": "CC0-1.0",
"extent": {
"spatial": {
"bbox": [
[
-180,
-90,
180,
90
]
]
},
"temporal": {
"interval": [
[
"1980-01-01T00:00:00Z",
"2009-12-31T23:59:59Z"
]
]
}
},
"summaries": {
"sci:doi": [
"10.5061/dryad.s2v81.2/27.2"
],
"sci:publications": [
{
"doi": "10.5061/dryad.s2v81.2",
"citation": "Vega GC, Pertierra LR, Olalla-Tárraga MÁ (2017) Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling. Dryad Digital Repository."
},
{
"doi": "10.1038/sdata.2017.78",
"citation": "Vega GC, Pertierra LR, Olalla-Tárraga MÁ (2017) MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling. Scientific Data 4: 170078."
}
]
},
"links": [
{
"rel": "self",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "item",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/item.json"
},
{
"rel": "root",
"href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/collection.json"
},
{
"rel": "cite-as",
"href": "https://doi.org/10.5061/dryad.s2v81.2"
}
]
}
59 changes: 46 additions & 13 deletions json-schema/schema.json
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Expand Up @@ -43,22 +43,52 @@
},
{
"$comment": "This is the schema for STAC Collections.",
"type": "object",
"required": [
"type"
],
"properties": {
"type": {
"const": "Collection"
}
},
"allOf": [
{
"type": "object",
"$ref": "#/definitions/stac_extensions"
}
],
"anyOf": [
{
"$comment": "This is the schema for the top-level fields in a Collection.",
"allOf": [
{
"$ref": "#/definitions/requirements"
},
{
"$ref": "#/definitions/fields"
}
]
},
{
"$comment": "This is the schema for the fields in Collection Assets.",
"required": [
"type"
"assets"
],
"properties": {
"type": {
"const": "Collection"
},
"assets": {
"type": "object",
"additionalProperties": {
"$ref": "#/definitions/fields"
}
},
}
}
},
{
"$comment": "This is the schema for the fields in Item Asset Definitions.",
"required": [
"item_assets"
],
"properties": {
"item_assets": {
"type": "object",
"additionalProperties": {
Expand All @@ -68,13 +98,16 @@
}
},
{
"$ref": "#/definitions/stac_extensions"
},
{
"$ref": "#/definitions/requirements"
},
{
"$ref": "#/definitions/fields"
"$comment": "This is the schema for the fields in Summaries.",
"required": [
"summaries"
],
"properties": {
"summaries": {
"type": "object",
"$ref": "#/definitions/requirements"
}
}
}
]
}
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