Time series data

Time series datasets act as containers for data points. All data points in a dataset share the same type and fields.

Additionally, all time series datasets include a few common fields. One of these fields, the time field, allows you to perform time-based data queries on a dataset.

​

Listing datasets

You can use your client instance to access the datasets available to you. For example, to access the sentinel1_sar dataset in the open_data.copernicus dataset group, use the following code.

Once you have your dataset object, you can use it to list the available collections for the dataset.

​

Common fields

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

These fields are present in all time series datasets. Together, they make up the metadata of a data point. Each dataset also has its own set of fields that are specific to that dataset.

​

Example data point

Below is an example data point from a time series dataset represented as an xarray.Dataset. It contains the common fields. When using the Tilebox Python client library, you receive the data in this format.

<xarray.Dataset>
Dimensions:         ()
Coordinates:
    time            datetime64[ns] 2023-03-12 16:45:23.532
    id              <U36 '0186d6b6-66cc-fcfd-91df-bbbff72499c3'
    ingestion_time   datetime64[ns] 2023-03-12 19:53:12.742
Data variables:
    *empty*