News about CEDAR

Try CEDAR Locally in Minutes: Dockerized Distribution Now Available

/in /by

We’re pleased to highlight the CEDAR Dockerized Distribution—a streamlined and developer-friendly way to deploy the entire CEDAR stack locally. Whether you’re evaluating CEDAR for the first time or preparing for a customized production setup, the Docker-based approach is designed to get you up and running with minimal effort.

What’s Included

The CEDAR Docker distribution includes a comprehensive docker-compose setup that brings together all the core components of the CEDAR ecosystem:

  • Infrastructure Services
    Core technologies such as MongoDB, Elasticsearch, Redis, and other foundational services.
  • CEDAR Microservices
    All key backend services for artifact management, user accounts, authentication, and metadata persistence.
  • Web Frontends
    The CEDAR Workbench, OpenView, and other browser-based tools, fully integrated and ready to use.
  • cedar-admin Tool
    A command-line utility for configuring and managing your CEDAR instance post-deployment.

Why Use the Docker Version?

Fast and Low-Cost Setup

With a single command, the full CEDAR platform can be deployed on a well-equipped developer machine in 20 to 40 minutes, depending on internet speed. It’s ideal for evaluation, demos, or local development environments.

Read more

HEAL Initiative Adopts CEDAR for FAIR Metadata Submission

/in /by

The NIH HEAL Initiative®—Helping to End Addiction Long-term—has integrated CEDAR into its data infrastructure to support the creation of machine-readable, standards-aligned metadata across its research projects. This integration supports the HEAL commitment to FAIR (Findable, Accessible, Interoperable, and Reusable) data practices.

CEDAR in the HEAL Metadata Submission Workflow

As part of the HEAL Platform’s SLMD (Study-Level Metadata) submission process, investigators are now required to submit structured metadata describing their studies, cohorts, and associated variables. To streamline this process and reduce technical overhead, the HEAL Platform provides a preconfigured CEDAR webform for metadata entry.

Read more

Empowering Rich Metadata Entry: How Dryad and OSF Are Using the CEDAR Embeddable Editor

/in /by

As scientific data sharing becomes increasingly vital to research transparency and reuse, the role of high-quality metadata has never been more important. Yet, creating structured, standards-aligned metadata remains a complex task—especially when researchers are forced to navigate unfamiliar tools or metadata standards outside their everyday workflows. That’s where the CEDAR Embeddable Editor (CEE) steps in.

Developed by the CEDAR team, the CEE is a lightweight, standards-compliant Web Component that enables third-party platforms to embed machine-actionable metadata templates directly into their interfaces. Instead of sending researchers off to external metadata portals, the CEE brings structured metadata authoring directly into the systems where scientists already work—lowering friction, improving consistency, and aligning with the FAIR principles.

Recently, two major research data platforms—Dryad and the Open Science Framework (OSF)—have integrated the CEE to enhance their metadata workflows.

Read more

ZonMw Recommends CEDAR for FAIR Metadata Creation

/in /by

The Netherlands Organization for Health Research and Development (ZonMw) is taking concrete steps to improve the FAIRness of COVID-19 and health research data. As part of its national guidance on metadata, ZonMw highlights CEDAR as a key tool for researchers to create machine-readable, reusable metadata.

FAIR Starts with Metadata

In ZonMw’s official Guidance on Metadata (v2.0), the organization emphasizes that rich, structured metadata are essential to making data findable and reusable. To this end, ZonMw asks all funded researchers to document seven key metadata elements, ranging from persistent identifiers and data formats to controlled vocabularies and metadata schemas.

The guidance makes it clear: metadata need to be both human- and machine-readable, ideally using RDF-based formats, and aligned with community standards.

Read more