What’s going on related to CEDAR?

CEDAR Now Supports DOI Minting with DataCite

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We’re pleased to announce that CEDAR users can now mint Digital Object Identifiers (DOIs) for their metadata templates and instances—directly from within the CEDAR platform. This new capability, developed in collaboration with the FAIR Workflows Project (https://datacite.org/implementing-fair-workflows-project/), enhances the visibility, permanence, and citability of the metadata authored in CEDAR.

A New Level of Metadata Publication

This integration with DataCite (https://datacite.org/), a leading DOI registration agency, enables CEDAR to treat metadata artifacts as first-class research outputs. Users can now publish finalized metadata templates and instances, assign them persistent identifiers, and make them discoverable through DataCite’s global infrastructure.

Importantly, DOI assignment is available only for published, versioned templates and instances—helping ensure that identifiers are reserved for complete, shareable resources.

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CEDAR Powers Machine-Actionable Metadata in M4M Workshops

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CEDAR is now a core tool in the GO FAIR Foundation’s Metadata for Machines (M4M) workshops—practical, community-driven events designed to accelerate the creation of FAIR, machine-actionable metadata.

What Is M4M?

The M4M workshop series brings together domain experts and metadata specialists to rapidly co-develop reusable, standards-aligned metadata templates for their communities (https://www.gofairfoundation.org/m4m/). The ultimate goal: produce machine-readable metadata that enables automated discovery, integration, and reuse of research data.

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Introducing CEDAR‑CLI: Streamlining Development and Deployment

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We’re excited to announce the release of CEDAR‑CLI, a Python‑based command‑line tool designed to simplify development, deployment, and release processes across the CEDAR ecosystem.

Why CEDAR‑CLI?

The CEDAR platform is large and complex. It spans approximately 50 Git repositories, with 15 microservices, 6 small front‑end projects, and 6 infrastructure services that work together to deliver the full functionality of the CEDAR Workbench. Managing these components manually has always been time‑consuming and error‑prone—until now.

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New Paper in Scientific Data: Modeling Community Standards as Metadata Templates

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We’re pleased to highlight the publication of a foundational paper from the CEDAR team in Scientific Data:
“Modeling community standards for metadata as templates makes data FAIR”
by Mark A. Musen, Martin J. O’Connor, Erik Schultes, and colleagues
📄 Read the paper

The Problem: Abstract Guidelines, Inconsistent Metadata

The FAIR principles (Findable, Accessible, Interoperable, and Reusable) have become central to modern research data policy—but implementing them at scale remains difficult. Many scientific domains have published metadata reporting guidelines, but these are typically in free-text form, making them difficult to apply in practice or enforce systematically.

The result? Metadata that is often inconsistent, incomplete, or lacking the semantic richness needed to enable true data reuse and discovery.

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