> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tilebox.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Spatio-temporal

> Spatio-temporal datasets associate each data point with both a timestamp and a geographic location on Earth, enabling queries that span time and space.

Each spatio-temporal dataset comes with a set of required and auto-generated fields for each data point.

## Required fields

While the specific data fields between different time series datasets can vary, there are common fields that all time series datasets share.

<ParamField path="time" type="Timestamp">
  The timestamp associated with each data point. Timestamps are always in UTC.
</ParamField>

<Tip>
  For indexing and querying, Tilebox truncates timestamps to millisecond precision. But Timeseries datasets may contain arbitrary custom `Timestamp` fields that store timestamps up to a nanosecond precision.
</Tip>

<ParamField path="geometry" type="Geometry">
  A location on the earth's surface associated with each data point. Supported geometry types are `Point`, `Polygon` and `MultiPolygon`.
</ParamField>

## Auto-generated fields

<ParamField path="id" type="UUID">
  A [universally unique identifier (UUID)](https://en.wikipedia.org/wiki/Universally_unique_identifier) that uniquely identifies each data point. IDs are generated so that sorting them lexicographically also sorts them by time.
</ParamField>

<Tip>
  IDs generated by Tilebox are deterministic, meaning that ingesting the exact same data values into the same collection will always result in the same ID.
</Tip>

<ParamField path="ingestion_time" type="Timestamp">
  The time the data point was ingested into the Tilebox API.
</ParamField>

## Creating a spatio-temporal dataset

To create a spatio-temporal dataset, use the [Tilebox Console](/console) and select `Spatio-temporal Dataset` as the dataset type. The required and auto-generated fields
already outlined will be automatically added to the dataset schema.

## Spatio-temporal queries

Spatio-temporal datasets support efficient time-based and spatially filtered queries. To query a specific location in a given time interval,
specify a time range and a geometry when [querying data points](/datasets/query/filter-by-location) from a dataset or a collection.

## Geometries

Handling Geometries can traditionally be a bit tricky, especially when working with geometries that cross the antimeridian or cover a pole.
Tilebox is designed to take away most of the friction involved in this, but it's still recommended to follow the [best practices for handling geometries](/datasets/geometries).