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Add Changelog (#52)
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changelog.mdx

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---
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title: Product Updates
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description: New updates and improvements
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description: New features, updates and improvements
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icon: rss
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---
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<Update label="May 2025">
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## Go Client
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<Frame>
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![Tilebox Go Client](/assets/changelog/2025-05-tilebox-banner-go.svg)
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</Frame>
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Excited to announce the release of the Tilebox Go client!
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**Features**
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- Datasets client
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- Statically typed dataset types
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- CLI to generate dataset types
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- Workflows client
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- Go task runners
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To get started, check out the [Go SDK documentation](/sdks/go/install).
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</Update>
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<Update label="April 2025">
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## Spatio-Temporal datasets
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<Frame>
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![Spatio-Temporal Datasets](/assets/changelog/2025-04-spatio-temporal.png)
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</Frame>
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Spatio-temporal datasets are officially out, fully supported in all languages and available as a category to create in custom datasets!
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The core problems that spatio-temporal datasets solve are
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- finding relevant data quickly (e.g. all Sentinel 2 granules along the US coastline, last year),
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- storing auxiliary geographically coded data (e.g. weather station data, ground truth data),
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- cataloging higher level data and results
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[Here's a short video](https://share.descript.com/view/khO3QJslhgU) on performance and core capabilities.
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We're excited about this as cataloging has until now been an unsexy but hard problem, and it's great to finally have a solution out there
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**More information**
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- [Spatio Temporal datasets documentation](https://docs.tilebox.com/datasets/types/spatiotemporal)
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- All open data now supports spatio-temporal queries
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- [Create your own spatio-temporal datasets](/guides/datasets/create)
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- [Ingesting spatio-temporal data](/datasets/ingest)
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</Update>
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<Update label="March 2025">
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## Custom Datasets
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Coming soon!
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<Frame>
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![Custom datasets](/assets/changelog/2025-03-custom-datasets.png)
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</Frame>
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Create your own custom datasets!
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- statically typed
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- with clients in Python and Go
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Use it to organize anything from telemetry, raw payload metadata, auxiliary sensor data, configuration data, or
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internal data catalogs.
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**Quickstart**
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1. Specify the data type in the Console
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2. Create a collection
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3. Use client.ingest() to ingest a `xarray.Dataset` or `pandas.DataFrame`
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4. Query away!
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For detailed instructions, check out the [Creating a dataset](/guides/datasets/create) how-to guide.
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</Update>

mint.json

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{
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"name": "API Reference",
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"url": "api-reference"
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},
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{
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"name": "Changelog",
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"url": "changelog"
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}
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],
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"primaryTab": {
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"api-reference/go/workflows/Jobs.Cancel",
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"api-reference/go/workflows/Jobs.List",
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"api-reference/go/workflows/Collect"
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]
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}
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]
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},
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{
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"group": "Changelog",
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"pages": [
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"changelog"
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]
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}
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],
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"feedback": {

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