Deploy on any machine running Docker using established deployment guides. Scale with Kubernetes as your needs grow.

Deploy behind your firewall or inside your VPN. Use your own compute for data processing and analysis tools.

Bring together and structure data from simulation codes, instruments, ELNs, LIMS, and other research systems.

Start with JupyterHUB, then add your own containerized tools with direct access to your data.

Extend NOMAD's core schema to create specialized editors for documenting your experiments and research workflows.

Keep data local, then selectively publish to the public NOMAD Central deployment.

Control your data and enforce your own policies: run inside your VPN, integrate existing user management, and choose who can access or publish.

Configure storage and backup to your requirements, including integration with existing institutional storage systems.

Use established deployment templates and guides, with standard procedures for configuration, updates, and backup.

Adapt data models, processing, ELNs, search interfaces, analysis tools, and integrations to your research needs.

Build on established schemas, parsers, plugins, and tools developed across the NOMAD community.

Contribute your developments and stay aligned with evolving, bottom-up community standards and practices.