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

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ESIIL Group 18: From Data Chaos to Community Standards

From Data Chaos to Community Standards

ESIIL Group 18's Journey Through the Metadata Maze

"Data on its own is not inherently useful — you need metadata and context. There's no problem that's not interdisciplinary, so it would be better if it wasn't so hard and time-intensive to collaborate." — heard in our discussion sessions

Our Journey: Navigating the Groan Zone

Two intensive days, 9 environmental scientists, one big challenge: making data work better for everyone.

🎯 Day 1: The Big Picture Problem

We started with grand ambitions—tackle all the data interoperability challenges in environmental science! But reality hit: we couldn't write a meaningful paper without understanding what researchers actually do with their data.

🤔 The Realization

Hurricane path data scattered across federal sources. Agricultural sampling methods buried in cryptic metadata. eDNA methods changing faster than we could keep up. The problem wasn't abstract—it was personal.

💡 Day 2: The Strategic Pivot

Instead of assuming solutions, we decided to ask the right questions first. What do researchers actually need? How do they currently handle metadata? What are the real barriers?

🛠️ Evidence-Based Solutions

Now we're building tools informed by real researcher needs: live polling at this summit, comprehensive post-event surveys, and practical guidelines for OASIS that actually work in the field. This evidence gathering is directly informing our perspectives paper for Environmental Data Science.

From Divergent Thinking to Convergent Action

We embraced the "Groan Zone" — that uncomfortable but creative space between brainstorming and decision-making.

Divergent Ideas

Best practices, training materials, repository audits, improving current repositories, creating ESIIL-Zenodo communities, developing data cube standards, AI tools for metadata generation — we explored everything

Groan Zone

Frustration led to breakthrough: we need data before prescribing solutions, we need to study the weaknesses of current initiatives, we can actually work on a solution to OASIS

Convergent Action

Tools to gather information, write a perspective paper, create resources for researchers

"Data usefulness goes down with time while costs go up — where's the sweet spot?"
— heard in our discussion sessions

What We're Building

📊 Live Community Polling

Right here at the summit — understanding how you identify datasets, what barriers you face, and where the biggest pain points lie in data discoverability.

Active Now

📝 Comprehensive Post-Survey

Detailed follow-up exploring metadata practices, repository usage, interoperability challenges, and time spent on data preparation across disciplines.

Coming Soon

📑 Call-to-Action Paper

Evidence-based recommendations for Environmental Data Science journal, targeting spring 2026 publication with concrete, actionable standards.

Spring 2026

🔧 OASIS Integration

Practical metadata guidelines and tools integrated into ESIIL's Open Analysis and Synthesis Infrastructure, making standards accessible where researchers actually work.

In Development

Why This Matters

🔍 The Hidden Time Sink

Researchers spend hours, days, even weeks hunting for datasets and preparing them for analysis. Imagine if that time could be spent on actual discovery instead.

🌐 The Interdisciplinary Imperative

Climate change doesn't respect disciplinary boundaries. Hurricane impacts involve meteorology, ecology, sociology, economics, and more. Our data should connect as easily as the problems do.

🚀 Future-Proofing Science

We can't predict what our data will be useful for in the future, but we can ensure it's equipped to be discovered, understood, and reused by the next generation of researchers.

Our Team Values in Action

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All Voices Welcome

We invite perspectives from every discipline

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Consensus-Building

We strive for solutions everyone can support

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Active Listening

Every perspective leads with curiosity

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Evidence-Based

We check our assumptions with real data

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AI-Transparent

We're open about how we use AI tools

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Dependable

We deliver on our commitments

Our Unique Approach

While most FAIR data initiatives create complex standards that are "challenging for typical researchers to understand and implement," we're taking a different path:

🏥 Learning from Success Stories

ESS-DIVE shows what's possible: high-quality standards, clear templates, rigorous quality control. We're studying what makes them successful and how to apply those lessons elsewhere.

👥 Community-Centric Design

Researchers first, standards second: Instead of top-down mandates, we're building from the ground up, understanding actual workflows and pain points.

🔬 Evidence-Based Development

Data about data practices: Our surveys and polls aren't just consultation — they're research that will inform practical, adoptable solutions.

🛠️ Implementation-Ready Tools

From theory to practice: Our OASIS integration ensures recommendations become accessible tools in researchers' actual workflows.

Join the Conversation

Your experience matters. Help us understand the real challenges and build better solutions.

Take Our Live Poll Join the Follow-up Survey

Together, we're not just managing data — we're accelerating discovery.



Team

Name Contact GitHub
Nilima Islam Luba nluba002@fiu.edu @nluba
Juan P. Maestre juanpedro.maestre@utexas.edu @DrMaestre
Sarah Cuprewich sarah.a.cuprewich.gr@dartmouth.edu @sajc36
Dana Gehring Danag@olc.edu @drg799802
Trisha Spanbauer trisha.spanbauer@uky.edu @trispan
Moriah Young youngmor@msu.edu@.edu @moriahy
Maricela Abarca mabarca@stanford.edu @myabarca
Nilima Islam Luba nluba002@fiu.edu @nluba
Sara Emery see68@cornell.edu @saraemery
Ed Hackett ehackett@asu.edu
Abdulganiyu Jimoh abdulganiyu.jimoh@usu.edu @Jimoh1993
And more (upcoming)!

Our norms as they were born

Our norms Raw photo location: assets/our_norms.png

Data management resources

Draft Google doc


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.