Share a reproducible stimulus description
Start from a checked Turtle example. Choose a profile, reuse exact SSTIM identifiers, and validate the file before publication.
Ontology →Python validation →SSTIM · learn by doing
Use SSTIM, from first concept to reproducible data.
A guided manual for scientists, application developers and AI users. Start with a browser, validate a stimulus description, record sessions from experiments, or connect your coding assistant to the released vocabulary.
SSTIM is an evolving knowledge reference. Its current implementation uses a formal ontology; the Workbench, clients and read-only MCP server are distinct tools around released knowledge. A structurally valid file is not evidence of physiological efficacy or actual device output.
Choose your route
Six practical guides
GUIDE 01
Use the Workbench
Explore concepts, query the graph and try reference patches.
GUIDE 02Reuse the ontology
Choose profiles, publish Turtle and retrieve versioned concepts.
GUIDE 03Python package
Validate RDF, choose profile closures and write session records.
GUIDE 04Node and browser package
Validate stimulus data and build session records in JavaScript.
GUIDE 05MCP for AI assistants
Give Codex, Claude, Copilot, Gemini and Cursor reference access to SSTIM.
GUIDE 06Work with the repository
Run the Workbench, validate examples and contribute reproducibly.
Practical outcomes
What can you build or learn?
Record sessions from research software
Turn experiment clocks and playback events from PsychoPy, jsPsych or Lab Streaming Layer into interoperable session records.
Python session builder →JavaScript session builder →Ground an AI assistant in released terms
Search, retrieve and compare versioned ontology terms, then ask an agent to map an existing data model without inventing SSTIM IRIs.
MCP use cases and installation →Explore the knowledge graph visually
Inspect concepts and named graphs; query the knowledge graph locally without setting up a SPARQL server.
Workbench tutorial →