By Jess Tate, Research Computer Scientist, Scientific Computing and Imaging (SCI) Institute, University of Utah 

The National Data Platform (NDP) (https://nationaldataplatform.org) is collaborative effort of teams from The Scientific Computing and Imaging (SCI), San Diego Supercomputing Center, and Univ. of Colorado and funded by the NSF (#2333609).  NDP is designed to revolutionize how researchers access, share, and work with data. Built to address long-standing challenges in data democratization, NDP offers a federated ecosystem that connects data sources, models, software, and compute resources—making them easier to find, use, and trust.  

Why NDP Matters 

Researchers often face barriers such as siloed data systems, inconsistent formats, and limited access to computing resources. NDP tackles these issues by creating a flexible, scalable infrastructure that supports both exploratory and advanced data workflows. 

Core Components 

• Central Hub: Hosts catalogs and collaborative workspaces where users can explore, share, and analyze data.   

• Endpoints: Customizable local deployments that bring processing closer to the data and allow users to tailor services to their needs. 

• Community NDP portals (cNDPs): Domain-specific interfaces that focus content and tools for particular research communities. 

Making Data FAIR and Usable 

NDP is built on the FAIR principles—Findable, Accessible, Interoperable, and Reproducible. It supports integration with national cyber infrastructure, cloud services, and AI workflows, while also offering interactive classrooms and data challenges for education. 

Advanced Discovery and Metadata 

• Flexible Metadata Schema: Supports diverse domains without enforcing rigid standards. 

• Contextual Search: Uses publication records to infer dataset usage and connect related resources. 

• Integration Examples: Includes partnerships with existing catalogs, such as the Marriot Library’s Hive (https://hive.utah.edu), to enhance discoverability at both local and national levels. 

Educational Tools 

NDP includes features for interactive learning, allowing educators to set up data-driven curricula and monitor student engagement. These tools help bridge the gap between data science and classroom instruction. 

Advanced Data Services for Non-Technical Users  

Leveraging the Science Data Exchange (SciDx) (https://scidx.sci.utah.edu), a software stack of advanced data services, NDP lowers the technical and resource barriers to deploying and accessing advanced data services such as: live data streaming, distributed memory management, and serverless computing.  NDP and SciDx allow researchers can process data in powerful new ways.    

Real-World Applications 

• Satellite Imagery: Enables in-memory filtering and selective downloading of large datasets like NOAA’s GOES satellite data. 

• Sensor Data Streaming: Supports live data ingestion and event detection from sources like Earthscope. 

• Smart Endpoints: Introduces AI agents that allow users to interact with data using natural language, simplifying complex workflows. 

Looking Ahead 

The platform continues to evolve, with new tools for metadata integration, domain-specific agents, and expanded dataset coverage. Whether you're a researcher, educator, or data librarian, NDP offers a powerful foundation for collaborative, scalable, and trustworthy data science. 

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