STAC Best Practices
11-04, 14:30–15:00 (America/New_York), Regency Ballroom B

This STAC 101 session covers the basics of STAC for users and data providers, explaining its core principles, metadata framework, and ecosystem. It includes lessons learned, practical tips, and guidance on using extensions and integrating STAC into geospatial workflows.


As the adoption of the SpatioTemporal Asset Catalog (STAC) continues to grow, understanding its core principles is essential for both users and data providers looking to leverage Earth observation data. This presentation will cover the foundational aspects of STAC, explaining how it enables better discovery, sharing, and analysis of geospatial assets through a unified metadata framework.

Attendees will learn about the core STAC specification, its key concepts, and the importance of its open-source ecosystem. We will highlight the role of STAC in overcoming data fragmentation in geospatial workflows, and how its extensibility supports a wide range of applications. Additionally, we’ll address lessons learned from early implementations and offer practical tips on how to use STAC effectively.

For data providers, this session will cover best practices for STAC adoption, including guidance on selecting the right extensions for different use cases. Users will also gain insight into how to query and explore STAC data efficiently. Whether you’re just starting with STAC or looking to deepen your understanding, this session will equip you with the knowledge needed to navigate and contribute to the growing STAC ecosystem.

Matt Hanson is the Director of Aerospace at Element 84, a commercial geospatial consultancy that utilizes open-source to build solutions. With an education in Remote Sensing at the Rochester Institute of Technology, he has been working with geospatial data for nearly 30 years. As an author and contributor to multiple open-source projects (starting with GeoNode in 2012), he has gone on to help create open standards, like STAC, as well as the open-source ecosystem around data interoperability.

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