Syllabus

09:15 - 09:30 | Introductions

09:30 - 10:30 | Lecture 1: Big Data in Environmental Policy

What problems do you work on? What data do you work with?

• Data infrastructures, data aggregation, data sovereignty
• Where data exist: platforms, APIs, cloud catalogs
• Introduction to STAC — what it is and why these infrastructures matter
• Data frictions: the gap between data availability and data access

10:30 - 10:45 | Break

10:45 - 11:45 | Activity 1: Finding Data in the STAC Catalog

Get into groups — start with the paper you read

• Look for the data described or needed in your paper inside a STAC catalog
• What infrastructures do these data live on? How big are they?
• What does it mean to access them? What frictions do you encounter?

11:45 - 12:00 | Share Back

• What frictions did you find? What surprised you?

12:00 - 13:30 | Lunch

13:30 - 14:15 | Lecture 2: Cloud-Native Computing and MCPs

• Working with data you cannot (or should not) download
• Cloud-native workflows: COGs, STAC queries, on-demand computation
• Introduction to Model Context Protocol (MCP) for data access — see MCP Servers page
• Live demo: STAC query and NDVI computation

14:15 - 14:45 | Explore: MCPs and Data Structures

Open exploration — doesn't have to be your group's paper topic

• Connect to an MCP server and run a query
• Explore what data structures and metadata are returned

14:45 - 15:00 | Break

15:00 - 15:30 | Projects and Deep Dives: Introduction

• Groups choose a dataset and policy question to investigate
• Framing: what would you actually need to answer this question?

15:30 - 16:30 | Group Work: Deep Dives

• Work through your chosen dataset and question
• Document what you found, what was hard, and what remains uncertain

16:30 - 16:45 | Report Back and Closing

• Brief group reports
• Closing reflection: What does it mean to do policy analysis in a world of planetary-scale, uneven, and infrastructure-dependent data?