Add collection link

examples/cyclone-wind-speed/collection.json

@@ -1,52 +1,52 @@
 {
-    "stac_version": "1.0.0",
-    "stac_extensions": [
-      "https://stac-extensions.github.io/ml-model/v1.0.0/schema.json"
-    ],
-    "type": "Collection",
-    "id": "model-cyclone-wind-estimation-torchgeo",
-    "title": "Tropical Cyclone Wind Speed Estimation Model",
-    "description": "Regression model that can be used to esimate the wind speed of a tropical cyclone based on a GOES image of the storm. This model was trained on the [Tropical Cyclone Wind Estimation Competition dataset](https://mlhub.earth/10.34911/rdnt.xs53up) using the [Torchgeo](https://github.com/microsoft/torchgeo) package.",
-    "license": "MIT",
-    "extent": {
-      "spatial": {
-        "bbox": [
-            [
-            -179.999,
-            -89.999,
-            179.999,
-            89.999
-            ]
-        ]
-      },
-      "temporal": {
-        "interval": [
-          [
-            "2000-01-01T00:00:00Z",
-            "2019-12-12T23:59:59Z"
-          ]
+  "stac_version": "1.0.0",
+  "stac_extensions": [
+    "https://stac-extensions.github.io/ml-model/v1.0.0/schema.json"
+  ],
+  "type": "Collection",
+  "id": "model-cyclone-wind-estimation-torchgeo",
+  "title": "Tropical Cyclone Wind Speed Estimation Model",
+  "description": "Regression model that can be used to esimate the wind speed of a tropical cyclone based on a GOES image of the storm. This model was trained on the [Tropical Cyclone Wind Estimation Competition dataset](https://mlhub.earth/10.34911/rdnt.xs53up) using the [Torchgeo](https://github.com/microsoft/torchgeo) package.",
+  "license": "MIT",
+  "extent": {
+    "spatial": {
+      "bbox": [
+        [
+          -179.999,
+          -89.999,
+          179.999,
+          89.999
         ]
-      }
-    },
-    "summaries": {
-      "ml-model:learning_approach": [
-        "supervised"
-      ],
-      "ml-model:prediction_type": [
-        "regression"
-      ],
-      "ml-model:architecture": [
-        "resnet18"
       ]
     },
-    "links": [
-      {
-        "href": "https://example.com/examples/collection.json",
-        "rel": "self"
-      },
-      {
-        "href": "./item.json",
-        "rel": "item"
-      }
+    "temporal": {
+      "interval": [
+        [
+          "2000-01-01T00:00:00Z",
+          "2019-12-12T23:59:59Z"
+        ]
+      ]
+    }
+  },
+  "summaries": {
+    "ml-model:learning_approach": [
+      "supervised"
+    ],
+    "ml-model:prediction_type": [
+      "regression"
+    ],
+    "ml-model:architecture": [
+      "resnet18"
     ]
-  }
+  },
+  "links": [
+    {
+      "href": "https://example.com/examples/collection.json",
+      "rel": "self"
+    },
+    {
+      "href": "./item.json",
+      "rel": "item"
+    }
+  ]
+}

examples/cyclone-wind-speed/item.json

@@ -70,16 +70,21 @@
   "links": [
     {
       "rel": "root",
-      "href": "./catalog.json",
+      "href": "./collection.json",
       "type": "application/json",
       "title": "Root Catalog"
     },
     {
       "rel": "parent",
-      "href": "./catalog.json",
+      "href": "./collection.json",
       "type": "application/json",
       "title": "Root Catalog"
     },
+    {
+      "rel": "collection",
+      "href": "./collection.json",
+      "type": "application/json"
+    },
     {
       "rel": "ml-model:inferencing-image",
       "href": "docker.io/radiantearth/cyclone-model-torchgeo:1",