This document explains the table Extension to the SpatioTemporal Asset Catalog (STAC) specification. It can be used with the projection extension to describe geospatial tabular data.
An Collection or Item can describe a tabular data assets, using a list of Column objects. Additionally, Collections can describe many tabular datasets using Table objects.
table:primary_geometry Is the column name of the "primary" or "active" geometry. This is used by libraries like geopandas and sf to control which geometry column is used. When a STAC item uses both the projection and table extensions, it's understood that the values in proj:espg, proj:bbox, etc. refer to the primary_geometry column.
Column objects contain information about each colum in the table.
Field Name Type Description name string REQUIRED. The column name description string Detailed multi-line description to explain the dimension. CommonMark 0.29 syntax MAY be used for rich text representation. type string Data type of the column. If using a file format with a type system (like Parquet), we recommend you use those types.The following fields can be used for assets (in the Asset Object).
table:storage_options can be used with fsspec to specify additional keywords necessary to open the data. For example, an asset might use {"account_name": "ai4edataeuwest"} to indicate that the asset is in the ai4edataeuwest storage account. Libraries like adlfs use this information to open the dataset.
The following fields apply only to Collections. They can be used to catalog a collection of tables, where each table is stored as an Item, without having to include column-level metadata from each table on the Collection.
Table objects contain high-level summaries about a table.
Field Name Type Description name string REQUIRED. The table name description string Detailed multi-line description to explain the dimension. CommonMark 0.29 syntax MAY be used for rich text representation.STAC allows for some flexibility in how to catalog assets. In general, we recommend using the following hierarchy:
Collection objects to catalog a dataset consisting of one or more tables.Item objects to catalog an individual table.For a dataset consisting of a single table or many tables with the same schema (for example gbif, which provides snapshots of the same database at different points in time), you might include table:columns on the Collection itself, or both the Collection and items.
For datasets with many tables (for example, USF Forest Inventory and Analysis), we recommend cataloging just the tables at the Collection level in table:tables, and cataloging the the columns at just the Item level in table:columns on each Item.
All contributions are subject to the STAC Specification Code of Conduct. For contributions, please follow the STAC specification contributing guide Instructions for running tests are copied here for convenience.
The same checks that run as checks on PR's are part of the repository and can be run locally to verify that changes are valid. To run tests locally, you'll need npm, which is a standard part of any node.js installation.
First you'll need to install everything with npm once. Just navigate to the root of this repository and on your command line run:
Then to check markdown formatting and test the examples against the JSON schema, you can run:
This will spit out the same texts that you see online, and you can then go and fix your markdown or examples.
If the tests reveal formatting problems with the examples, you can fix them with:
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