New Paper in Scientific Data: How CEDAR Enables Standardized Metadata Across HuBMAP—and Now SenNet

We’re pleased to announce the publication of a new paper in Scientific Data titled
“Ensuring Adherence to Standards in Experiment-Related Metadata Entered Via Spreadsheets”
(Read the paper).

This paper outlines how the CEDAR Workbench has played a central role in ensuring that experiment-related metadata collected by the HuBMAP consortium adheres to FAIR principles and community standards—despite being entered by researchers using spreadsheets. It also describes the expansion of this approach into the SenNet program, demonstrating how metadata consistency and quality can scale across large, decentralized biomedical research consortia.

The Challenge: Researcher-Friendly Interfaces with Standards-Driven Metadata

Biomedical consortia like HuBMAP face a major challenge: researchers need to enter metadata that is rich, precise, and standards-compliant—but they overwhelmingly prefer working in spreadsheets. This poses a tension between usability and data quality.

Rather than force researchers to abandon familiar tools, the CEDAR team collaborated with HuBMAP to design a solution that lets researchers continue using spreadsheets while ensuring the underlying metadata adheres to formal standards.

CEDAR-Powered Metadata Management in HuBMAP

The paper details how HuBMAP used the CEDAR Workbench to create more than 30 structured metadata templates covering biospecimen collection, assays, and tissue processing. These templates are:

• Backed by community ontologies like OBI, UBERON, CL, and EDAM
• Semantically explicit, with field-level constraints, validation, and ontology term selection
• Output in JSON-LD, enabling downstream integration and discovery

CEDAR’s infrastructure then generates annotated spreadsheet templates from these metadata forms. Researchers fill these out in Excel or Google Sheets, but each cell corresponds to a well-defined field from the CEDAR metadata model.

Once filled, the spreadsheets are programmatically validated and converted back into structured JSON-LD via the CEDAR API—ensuring data integrity while accommodating researchers’ workflow preferences.

Integration Across HuBMAP

The result is a full-stack metadata ecosystem where:

• Templates are collaboratively authored in CEDAR
• Researchers fill out intuitive spreadsheets
• Data managers validate and ingest the metadata automatically
• Outputs are standards-aligned and machine-actionable

This approach is now operational across HuBMAP’s 60+ data contributors, ensuring consistency without sacrificing usability.

Scaling to SenNet

The SenNet consortium, which focuses on senescent cell profiling across human tissues, is now adopting this same strategy. CEDAR-based templates have been adapted for SenNet’s unique metadata needs, and the spreadsheet-based entry pipeline is being reused to accelerate onboarding and minimize errors.

The paper outlines how early SenNet metadata—also entered via spreadsheets—is already conforming to ontology-backed, reusable formats via CEDAR’s validation and transformation tools.

A Practical FAIR Metadata Blueprint

This work shows that it’s possible to marry the simplicity of spreadsheet entry with the rigor of standards-based metadata. By placing CEDAR at the center of this pipeline, both HuBMAP and SenNet have made structured metadata entry accessible, scalable, and FAIR-compliant.

For other research networks grappling with metadata chaos, this publication offers a compelling blueprint: standards adherence and ease-of-use don’t have to be tradeoffs.