
Galaxy Project
The open-source ecosystem for data-intensive science, workflow automation, and reproducible research.

The computational science platform for reproducible research and automated R&D workflows.

Code Ocean is a specialized computational science platform designed to solve the 'reproducibility crisis' in technical research. At its core is the 'Compute Capsule'—a containerized unit that encapsulates code, data, environment, and results, ensuring identical execution across any infrastructure. In the 2026 landscape, Code Ocean has solidified its position as the standard for Life Sciences and Biotech firms, bridging the gap between bench scientists and computational researchers. Its architecture leverages Docker and Kubernetes to provide a language-agnostic environment supporting R, Python, Julia, MATLAB, and C++. The platform integrates seamlessly with cloud providers (AWS, GCP, Azure) to offer scalable compute while maintaining strict data lineage and provenance. By automating the configuration of complex dependencies through its environment builder, Code Ocean reduces the technical overhead for researchers, allowing them to focus on scientific discovery rather than DevOps. It serves as a centralized hub for collaborative R&D, enabling teams to share validated workflows and meet FAIR (Findable, Accessible, Interoperable, Reusable) data principles mandated by regulatory bodies and funding agencies.
Code Ocean is a specialized computational science platform designed to solve the 'reproducibility crisis' in technical research.
Explore all tools that specialize in automate scientific workflows. This domain focus ensures Code Ocean delivers optimized results for this specific requirement.
Explore all tools that specialize in track data lineage. This domain focus ensures Code Ocean delivers optimized results for this specific requirement.
Explore all tools that specialize in scientific workflow automation. This domain focus ensures Code Ocean delivers optimized results for this specific requirement.
Self-contained executable packages containing code, data, and environment metadata using Docker.
Automatic tracking of all data transformations, code versions, and environment changes during every run.
Abstracts cloud infrastructure, allowing the same capsule to run on AWS, GCP, or local HPC.
A GUI for managing Linux dependencies, Conda environments, and R packages without writing Dockerfiles.
Bi-directional synchronization between the Compute Capsule and external Git repositories.
Spin up JupyterLab, RStudio, or Shiny apps directly within the capsule environment.
Support for mounting massive read-only datasets via S3 or local network drives without copying data.
Create an account via SSO or email and set up your research workspace.
Initialize a new Compute Capsule from a template or by importing a Git repository.
Configure the computational environment by selecting a base image (e.g., Ubuntu, RStudio, Jupyter).
Define package dependencies using the point-and-click package manager for Conda, CRAN, or PyPI.
Upload raw data or link external storage buckets (AWS S3, Azure Blob) to the capsule's data folder.
Draft or import computational scripts within the built-in IDE or sync via local VS Code extension.
Set the main entry point script and define execution parameters in the capsule metadata.
Trigger a test run to build the Docker image and verify environment stability.
Analyze output results, logs, and automatically generated provenance records.
Publish the capsule with a persistent DOI or share it privately with collaborators for peer review.
All Set
Ready to go
Verified feedback from other users.
"Highly praised for its ability to eliminate 'it works on my machine' problems in scientific research. Users value the integrated environment management and DOI minting features."
Post questions, share tips, and help other users.

The open-source ecosystem for data-intensive science, workflow automation, and reproducible research.

Metadata Context Platform for Data & AI, delivering AI-ready data through automated cataloging, lineage, and semantic models.

The leading secure, collaborative, and compliant cloud-based Electronic Lab Notebook for modern scientific research.

The first end-to-end Data Observability Platform for AI-ready data reliability.

The world’s first remotely operated life sciences laboratory.

A unified control plane for building, scaling, and observing AI and data pipelines.