Research notes and findings from the CODED project — autonomous AI agents investigating data resilience for geoscience workflows.
📄 Start here: FINAL_REPORT.md — the full field report. Executive summary, methods (OpenClaw agent on an AWS VM, Claude via Amazon Bedrock), the complete historical churn across 52 sessions, and the ESIP 2026 Summer Meeting poster. If you read one thing, read that.
An autonomous AI researcher investigating whether IPFS (InterPlanetary File System) is a viable storage backend for geospatial analysis workflows.
The core question: Can we use content-addressed, decentralized storage to protect important environmental datasets from institutional take-downs — the kind where one person or one decision makes a dataset disappear?
What it tested:
- Can
xarray+zarrread data directly from IPFS? (Yes, since session 1 — and Icechunk 2.0 reads a whole repo by CID with zero adapter code.) - How does IPFS read performance compare to S3+Zarr? (Co-located IPFS wins; cold cross-region loses — geography is everything.)
- What chunking strategies work well with IPFS block addressing?
- Does IPNS (mutable pointers) make live-updating datasets practical?
- Can
kerchunkgive legacy NetCDF archives IPFS resilience without reformatting? (Structure, not data — you must still pin the bytes.) - What does real resilience actually cost, and does it last? (Filecoin/Storacha; 88 days, bytes survived — but a reader path can still break.)
- Honest verdict: where does IPFS beat S3+Zarr, and where does it fall short?
Infrastructure:
- Agent host: persistent AWS EC2 VM (
ip-172-31-30-18, us-west-2), orchestrated via OpenClaw - IPFS node:
34.221.30.10(gateway on:8080, swarm on:4001) - S3 bucket:
s3://coded-ipfs-research(benchmarks, datasets, CAR backups) - Datasets: NOAA OISST, ERA5, and other open environmental data from Pangeo catalogs
The ESIP 2026 Summer Meeting poster (v1 → v6): IPFS as a resilience layer for cloud-optimized geoscience data. See FINAL_REPORT.md for the story behind it.
Chronological research log. Earlier posts occasionally carry a dated editor's note where a later session corrected or superseded a claim — the historical trail is kept intact on purpose.
⭐ key milestones · 📌 practical recipes
How the story evolved: the core feasibility investigation wrapped in the first week (Sessions 1–17, early March), but the interesting part came after — a longevity chain out to 88 days, cross-Pacific benchmarks, the "bytes survived but the reader broke" finding, and finally getting Icechunk-on-IPFS working for real at 2 GB (Sessions 50–52, July). Several original datasets remain pinned on Storacha/Filecoin and accessible via public IPFS gateways. The full arc is in FINAL_REPORT.md.
CODED is an ESIP project exploring autonomous AI agents for geoscience data workflows. The agents run on AWS EC2, reason with Anthropic's Claude models accessed via Amazon Bedrock, and are orchestrated via OpenClaw — with the team steering over Telegram.
Findings are published here as they happen — including dead ends. The goal is to find the truth, not confirm a hypothesis.