OneSciencePlace (OSP) is a composable platform in active pilot deployment across institutional and national-scale projects. This roadmap outlines the platform areas we are developing next: expanding capabilities, deeper integrations, and open-source community distribution, while maintaining the simplicity, openness, and sustainability that define OSP today.

OSP Today

OSP is currently available as a fully managed service with active pilot deployments underway covering applications, compute integration, data sharing, FAIR publishing, identity and access management, and content management. OSP is being deployed across a growing range of institutional contexts — science gateways, campus HPC portals, national-scale resources, lab environments, and instructional computing — demonstrating the platform's versatility across the research and education landscape.

An open-source distribution is in active development. Explore current platform capabilities

OSP 2.0 Vision

OSP 2.0 represents the next major evolution of the platform, moving from a composable delivery environment to a fully integrated research operating environment. The following capabilities define the 2.0 vision.

Workflow Orchestration

A visual, event-driven workflow composer enabling researchers to build and run multi-step, multi-application pipelines across heterogeneous compute systems. Workflows will be reusable, versioned, and integrated with OSP's provenance and publishing infrastructure — enabling end-to-end reproducible research directly from the platform.

FAIR Data Publishing

A technically rigorous implementation of FAIR principles, drawing on fairsharing.org as a model for standardized metadata schemas, controlled vocabularies, and interoperability standards. FAIR implementation in OSP 2.0 will be discipline-aware — providing a common extensible foundation while supporting domain-specific metadata schemas, vocabularies, and curation workflows configured per deployment.

Kubernetes and AI/ML Workloads

Expanded compute integration supporting Kubernetes-based job execution, interactive GPU sessions, and AI/ML workflows. This will enable OSP deployments to support modern machine-learning and data-intensive workloads alongside traditional HPC batch jobs — within the same unified interface.

Collaborative Group Spaces

Shared environments for research teams, classes, and projects to organize resources, manage members, and publish results together. Group spaces will support delegated administration, group-level access controls, and policy-based permissions across all platform capabilities.

Learning Management Integration

Integration with Canvas LMS enabling instructors to deploy advanced computational environments for coursework — beyond the Jupyter ecosystem. Course rosters map directly to OSP groups, enabling scalable, reproducible instructional computing on campus, cloud, or HPC resources.

Unified Research Dashboard

A single administrative and researcher-facing dashboard for managing projects, applications, data, jobs, workflows, and publications — designed for clarity, low cognitive load, and productivity across all OSP capabilities.

External API Layer

A programmable API layer enabling automation, interoperability, and integration with external tools and services. This will allow institutions and developers to build on OSP's capabilities programmatically rather than exclusively through the web interface.

Open-Source Community Distribution

A structured public release of the unified OSP distribution, enabling institutions to self-host, contribute, and adapt the platform to their specific infrastructure and community needs.

Learn more about the open-source roadmap

Our Focus

Make advanced cyberinfrastructure easier to use, adaptable across disciplines, and sustainable through open community development — transforming how research and education connect with computation and data.

Interested in contributing to OSP's development or discussing the roadmap? Contact the OSP team