top of page
DeCODER Logo_edited.jpg
Democratized Cyberinfrastructure for Open Discovery to Enable Research

Standardize how scientific data is described

  • Allow search engines for scientific data to support discoverability AND

  • Facilitate the usage of the data

The new NSF CSSI Democratized Cyberinfrastructure for Open Discovery to Enable Research (DeCODER) project will expand and extend the successful EarthCube GeoCODES framework and community to unify data and tool description and reuse across geoscience domains.  (See announcement.)

Adoption of science-on-schema


The internet works because of defined standards and protocols (e.g. TCP/IP, HTTP, HTML). This allows software, which must be sustained, to change and evolve over time, with better software with new features to emerge (e.g. new browsers, new web servers), while still allowing everything to just work from the user perspective.

That’s what we are doing here for research data through the adoption of science-on-schema.

DeCODER will continue to partner with ESIP and the Council of Data Facilities with the adoption of this standard across the partnering geoscience data centers, building search aggregators that can now crawl data center collections and  construct a centralized index by which users, or other software through a provided API, can find data of interest across all available sources.

Image by Gatis Marcinkevics

Science applications 


To understand and address critical geosciences challenges we must find and leverage data and tools from across national and international facilities and programs. While building a flexible and extensible framework to fit many geosciences domains, the DeCODER project will also work with three specific communities, to ensure a tight connection to real science needs:

  • low-temperature geochemistry

  • ecological forecasting

  • deep ocean observing


Center for Ecosystem Forecasting


The Center develops tools that forecast everyday services provided by ecosystems, like water quality, forest production, and more. They develop and deploy environmental sensors, build robust ecological models, and work closely with forecast users to co-create tools that can guide decision-making on human health and well-being. Their goal is to develop reliable forecasts and intuitive visualizations that protect our communities and advance our understanding of ecosystems. 

Learn more


PODCAST - Open Geo AI:

Unveiling Satellite Insights through Open Data 


In this podcast , Tao Wen and Carl Boettiger share real-life success stories at the intersection of open data, AI, and satellite information. From ML models for land-water systems to open science initiatives, explore how diverse sectors leverage time series models, R environments, and NASA's Open Scripts project on AWS Cloud for transformative decision-making.

Listen to this episode and others in the series here.


agu 2023.webp



Kenton McHenry


NCSA-University of Illinois


Shuang Zhang

Biochemical Cycles

Texas A&M University


Christine Kirkpatrick


SDSC-UC San Diego


Quinn Thomas


Virginia Tech

karen stocks.jpg

Karen Stocks

Ocean Science

SIO-UC San Diego


Carl Boettiger


UC Berkeley


Tao Wen


Syracuse University


Lynne Schreiber


SDSC-UC San Diego

nsf logo.jpg

This work is supported through the National Science Foundation award # 2209863.

bottom of page