Welcome to the SDL Documentation
The Scientific Data Layer (SDL) provides a flexible and extensible ecosystem for managing scientific data using linked data principles, semantic web technologies, and modular microservices. This documentation is your guide to understanding, using, and extending SDL as a platform for FAIR data and collaborative research.
Overview
SDL helps
- Organize data and metadata semantically using RDF and standard ontologies
- Track provenance, workflows, and content structure
- Enable collaborative editing within workspaces
- Deploy modular services for cataloging, storage, and content management
- Build reusable and dynamic UIs with semantic awareness
Whether you're a researcher, data curator, developer, or administrator, this documentation provides targeted guidance for your role.
User Documentation
For researchers, authors, data stewards, and other users working within the SDL interface.
- User Guide: Learn how to log in, create content, and navigate workspaces
- Workspaces & Navigation: Organize your projects and data semantically
- Semantic Content Blocks: Use and annotate typed blocks of content
Deployment
For everyone...
- Platform Survey: Learn how to gather the information necessary to create a new platform
Developer Documentation
For platform engineers, backend developers, UI integrators, and data engineers contributing to or building on SDL.
- Architecture Overview: Understand the modular design and service boundaries
- Backend Architecture Overview:Overview of scalable scientific data management across a system-of-systems (SoS) architecture
- API Reference: Endpoints for interacting with SDL services
- Ontology Integration: Use, extend, and align domain ontologies
- RDF Ontologies in SDL: Overview of core and extended vocabularies
- Semantic Classes: Common resource types and how they shape the UI
Need Help?
We're glad you're here. Let's build better science, together.