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Cross-Cutting Data Interoperability & Harmonization Innovation Summit 2025 — Group 18

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Wide banner of the study system Raw photo location: assets/esiil_art/paperclip.png

One sentence on impact: In three days, Group 18 is prototyping cross-cutting interoperability workflows that let partners combine climate, ecological, and social datasets without friction.

Summit concept note (PDF) · View shared code · Explore data

About this site: This is a living notebook for the Cross-Cutting Data Interoperability & Harmonization Innovation Summit 2025. Group 18 captures decisions, visuals, and code here so partners can follow along in real time.

How to use this page (for the team)

  • Edit this file: docs/index.md → ✎ → change text → Commit changes.
  • Add images: upload to docs/assets/ and reference like assets/your_file.png.
  • Keep text short and visuals first. Think “slide captions,” not essays.

Day 1 — Define & Explore

Focus: questions, hypotheses, context; add at least one visual (photo of whiteboard/notes).

Our product 📣

-A call to action for broader community change/standards - a paper for standards in metadata to future-proof data to ensure future utility. We can't imagine what our data can be useful for in the future. How can we generalize across our disciplines? Maybe special issue Environmental Data Science, ideas by Nov 2025, full article by spring 2026 - an open source tool that translates the academic paper

Our question(s) 📣

  • Can we use AI/LLMs for identifying if datasets are fit for use?
  • Can we do a review of the metadata standards that exist for FAIR data principles or siloed projects (coping with FAIR Maricela)
  • We have to behave differently before we can even get to FAIR

Hypotheses / intentions

  • usefulness of data goes down and cost goes up
  • museum/library/archival perspective on data accessibility over time versus data scientist view on data is "useful/accessible" for 5 years max

Why this matters (the “upshot”) 📣

  • in order to operationalize FAIR we have to have community standards that everyone adheres to (DARE?)
  • for such a data centric group
  • data isn't "useful" broadly to the community
  • standardizing the standards
  • there's no problem that's not interdisciplinary, it might be better if we have broader community standards

Inspirations (papers, datasets, tools)

Field notes / visuals

Our norms Raw photo location: assets/our_norms.png Caption: Mapping current interoperability pain points, user stories, and priority partners for Group 18.

Different perspectives: Briefly capture disagreements or alternate framings. These can unlock innovation.

Day 2 — Data & Methods

Focus: what we’re testing and building; show a first visual (plot/map/screenshot/GIF).

Data sources we’re exploring 📣

  • NOAA Climate Data Online (CDO) — hourly precipitation and temperature summaries that we will harmonize with partner-held observations.

Pattern revealed during exploration Raw photo location: explore_data_plot.png Snapshot highlighting how CDO variables vary across pilot watersheds.

  • USGS Water Services API — near real-time streamflow indicators to pair with ecological and community datasets for interoperability testing.

Methods / technologies we’re testing 📣

  • Metadata crosswalks and schema mapping powered by frictionless data packages.
  • Automated vocabulary translation notebooks (Python) that align partner terminology.
  • Visualization prototypes that compare harmonized and raw feeds for quick QA/QC checks.

Challenges identified

  • Differing temporal resolutions make alignment tricky without resampling guidance.
  • Some partner feeds lack machine-readable metadata, requiring manual curation.
  • We still need to prioritize which interoperability blockers are most urgent for downstream users.

Visuals

Static figure

Early pattern we’re seeing Raw photo location: figure1.png Figure 1. Prototype dashboard showing how harmonized schema fields resolve unit mismatches between sources.

Animated change (GIF)

Seasonal/temporal change animation Raw photo location: change.gif Figure 2. Animated QA/QC workflow illustrating how harmonized feeds track anomalies through time.

Interactive map (iframe)

Open full map

If an embed doesn’t load, put the normal link directly under it.

Final Share Out — Insights & Sharing

Focus: synthesis; highlight 2–3 visuals that tell the story; keep text crisp. Practice a 2-minute walkthrough of the homepage 📣: Why → Questions → Data/Methods → Findings → Next.

Team photo at start of Day 3 Raw photo location: team_photo.jpg

Findings at a glance 📣

  • Harmonized schemas cut manual data-mapping time by 40% in our pilot workflow.
  • Automated vocabulary translation enabled two agencies to align QA/QC flags in a single notebook run.
  • Shared data contracts clarified stewardship roles, unlocking commitments to sustain the service beyond the summit.

Visuals that tell the story 📣

Lead interoperability graphic Raw photo location: fire_hull.png Visual 1. Overview of the harmonized schema showing how climate and hydrology feeds now share common field definitions.

Supporting panels for key insights Raw photo location: hull_panels.png Visual 2. Comparison of partner vocabularies before and after applying the translation templates.

Complementary result figure placeholder Raw photo location: main_result.png Visual 3. Dashboard mock-up illustrating how interoperable feeds flow into decision-ready summaries.

What’s next? 📣

  • Finalize documentation for the interoperability playbook and publish version 1.0 to the repo.
  • Meet with summit partners to prioritize which additional datasets join the harmonization pipeline.
  • Schedule a spring 2025 workshop to onboard new collaborators to the shared workflows.
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Team

Name Role Contact GitHub
Add your team lead Coordination & partner outreach email@example.org @github-handle
Add your data lead Data acquisition & metadata email@example.org @github-handle
Add your methods lead Workflow prototyping email@example.org @github-handle
Add your comms lead Storytelling & visuals email@example.org @github-handle

Storage

Code Keep shared scripts, notebooks, and utilities in the code/ directory. Document how to run them in a README or within the files so teammates and visitors can reproduce your workflow.

Documentation Use the docs/ folder to publish project updates on this site. Longer internal notes can live in documentation/; summarize key takeaways here so the public story stays current.

Cite & reuse

If you use these materials, please cite:

ESIIL Innovation Summit Team 18. (2025). Cross-Cutting Data Interoperability & Harmonization Innovation Summit 2025 — Group 18. https://github.com/CU-ESIIL/cross-cutting-data-interoperability-harmonization-innovation-summit-2025__18

License: CC-BY-4.0 unless noted. See dataset licenses on the Data page.