diff --git a/api-reference/tilebox.datasets/Collection.delete.mdx b/api-reference/tilebox.datasets/Collection.delete.mdx
new file mode 100644
index 0000000..43ae441
--- /dev/null
+++ b/api-reference/tilebox.datasets/Collection.delete.mdx
@@ -0,0 +1,34 @@
+---
+title: Collection.delete
+icon: download
+---
+
+```python
+def Collection.delete(datapoints: xr.Dataset) -> int
+```
+
+Delete datapoints from the collection.
+
+Datapoints are identified and deleted by their ids.
+
+
+ You need to have write permission on the collection to be able to delete datapoints.
+
+
+## Parameters
+
+
+ An [`xarray.Dataset`](/sdks/python/xarray) containing an "id" variable consisting of datapoint IDs to delete.
+
+
+## Returns
+
+The number of datapoints that were deleted.
+
+
+```python Python
+datapoints = collection.load("2023-05-01 12:45:33.423")
+
+n_deleted = collection.delete(datapoints)
+```
+
diff --git a/api-reference/tilebox.datasets/Collection.delete_ids.mdx b/api-reference/tilebox.datasets/Collection.delete_ids.mdx
new file mode 100644
index 0000000..efdfc14
--- /dev/null
+++ b/api-reference/tilebox.datasets/Collection.delete_ids.mdx
@@ -0,0 +1,36 @@
+---
+title: Collection.delete_ids
+icon: download
+---
+
+```python
+def Collection.delete_ids(datapoints_ids: list[UUID]) -> int
+```
+
+Delete datapoint from the collection by their ids.
+
+
+ You need to have write permission on the collection to be able to delete datapoints.
+
+
+## Parameters
+
+
+ The ids of the datapoints to delete.
+
+
+## Returns
+
+The number of datapoints that were deleted.
+
+
+```python Python
+from uuid import UUID
+
+datapoints_ids=[
+ UUID("29b29ade-db02-427a-be9c-a8ef8184f544"),
+ UUID("fa4a8e4e-6afe-41a3-b228-b867330669bd"),
+]
+n_deleted = collection.delete_ids(datapoints_ids)
+```
+
diff --git a/datasets/ingest-delete-data.mdx b/datasets/ingest-delete-data.mdx
new file mode 100644
index 0000000..1c85149
--- /dev/null
+++ b/datasets/ingest-delete-data.mdx
@@ -0,0 +1,75 @@
+---
+title: Ingesting and Deleting Data
+sidebarTitle: Ingesting and deleting data
+description: Learn how to ingest and delete data from Time Series Dataset collections.
+icon: download
+---
+
+## Overview
+
+This section provides an overview of the API for ingesting and deleting data from a collection. It includes usage examples for many common scenarios.
+
+| Method | API Reference | Description |
+| ----------------------- | ------------------------------------------------------------------------------------ | ---------------------------------------------------- |
+| `collection.delete` | [Deleting data points](/api-reference/tilebox.datasets/Collection.delete) | Delete data points from a collection. |
+| `collection.delete_ids` | [Deleting data points by IDs](/api-reference/tilebox.datasets/Collection.delete_ids) | Delete data points from a collection by their ids. |
+
+
+ You need to have write permission on the collection to be able to ingest or delete datapoints.
+
+
+Check out the examples below for common scenarios when ingesting and deleting data from collections.
+The examples assume you have already [created a client](/datasets/introduction#creating-a-datasets-client) and [accessed a specific dataset collection](/datasets/collections) that you have write permissions on.
+
+
+```python Python
+from tilebox.datasets import Client
+
+client = Client()
+datasets = client.datasets()
+collections = datasets.open_data.copernicus.sentinel1_sar.collections()
+collection = collections["S1A_IW_RAW__0S"]
+```
+
+
+## Ingesting data
+
+
+## Deleting data
+
+To delete data from a collection, use the [delete](/api-reference/tilebox.datasets/Collection.delete) or [delete_ids](/api-reference/tilebox.datasets/Collection.delete_ids) method.
+
+One common way to delete data is to load it from a collection and then forward it to the `delete` method.
+
+
+```python Python
+datapoints = collection.load(("2023-05-01", "2023-06-01"))
+
+n_deleted = collection.delete(datapoints)
+print(f"Deleted {n_deleted} data points.")
+```
+
+
+```plaintext Output
+Deleted 104 data points.
+```
+
+In case you already have the list of datapoint IDs that you want to delete, you can use the `delete_ids` method.
+
+
+```python Python
+from uuid import UUID
+
+datapoints_ids=[
+ UUID("29b29ade-db02-427a-be9c-a8ef8184f544"),
+ UUID("fa4a8e4e-6afe-41a3-b228-b867330669bd"),
+]
+
+n_deleted = collection.delete_ids(datapoints_ids)
+print(f"Deleted {n_deleted} data points.")
+```
+
+
+```plaintext Output
+Deleted 2 data points.
+```
diff --git a/datasets/open-data.mdx b/datasets/open-data.mdx
index a1e172c..4524270 100644
--- a/datasets/open-data.mdx
+++ b/datasets/open-data.mdx
@@ -20,7 +20,7 @@ By using the [datasets API](/datasets), you can start prototyping your applicati
## Available datasets
- The Tilebox Console contains in-depth descriptions of each dataset, including many code-snippets to help you get started. Check out the [Sentinel 5P Tropomi](https://console.tilebox.com/datasets/descriptions/feb2bcc9-8fdf-4714-8a63-395ee9d3f323) documentation as an example.
+ The Tilebox Console contains in-depth descriptions of each dataset. Check out the [Sentinel 5P Tropomi](https://console.tilebox.com/datasets/explorer/feb2bcc9-8fdf-4714-8a63-395ee9d3f323?view=documentation) documentation as an example.
### Copernicus Data Space
diff --git a/mint.json b/mint.json
index 3f7f3f0..7178c93 100644
--- a/mint.json
+++ b/mint.json
@@ -104,6 +104,7 @@
"datasets/timeseries",
"datasets/collections",
"datasets/loading-data",
+ "datasets/ingest-delete-data",
{
"group": "Managed datasets",
"icon": "bars-progress",
@@ -163,7 +164,9 @@
"api-reference/tilebox.datasets/Dataset.collection",
"api-reference/tilebox.datasets/Collection.info",
"api-reference/tilebox.datasets/Collection.load",
- "api-reference/tilebox.datasets/Collection.find"
+ "api-reference/tilebox.datasets/Collection.find",
+ "api-reference/tilebox.datasets/Collection.delete",
+ "api-reference/tilebox.datasets/Collection.delete_ids"
]
},
{