overview

name	overview
description	What TVBO is — the three pillars (LinkML datamodel, ontology, Python package) plus the Odoo platform. Use when working with the tvbo library or deciding whether to reach for it.
metadata	{"audience":"user","applies_to":["**"],"tags":["overview","orientation"],"requires_extras":[]}

TVBO Overview

TVBO (The Virtual Brain Ontology) is a knowledge-representation and simulation toolkit for large-scale brain network models. It consists of three pillars plus a platform.

Pillar 1 — LinkML datamodel

schema/*.yaml defines the structured metadata for SimulationExperiment, SimulationStudy, Dynamics, Network, Atlas, and friends. The Python types in tvbo/datamodel/ are generated from this schema. Users consume them through the higher-level classes in tvbo/classes/.

Pillar 2 — Ontology

tvb-o.owl and the TTL/SHACL files in ontology/ carry the axioms about:

• SimulationExperiment and SimulationStudy
• Network and DynamicalSystem
• Software used to specify and run Dynamical Network Models

Loaded via owlready2 from tvbo.ontology.

Pillar 3 — Python package

The tvbo Python package does four things:

1. Specifies models — Dynamics, Equation, Network, etc. as Python objects or YAML files.
2. Loads SimulationExperiments, SimulationStudys, and all other ontology-backed classes.
3. Generates code for all supported backends (JAX, NumPy, TVB, Julia/DifferentialEquations.jl, PyRates, ModelingToolkit, NetworkDynamics, NeuroML, …).
4. Executes the generated code and runs experiments against the chosen backend.

Entry points: from tvbo import Dynamics, SimulationExperiment. See the writing-models and running-simulations skills for the everyday workflows.

Platform — tvbo.charite.de

An Odoo-based management layer over the ontology. Users can:

• Display knowledge stored in the ontology and the curated models.
• Retrieve knowledge programmatically.
• Set up their own models, store and share SimulationExperiments / SimulationStudys (public by default; private with an API key).
• Load shared experiments back into Python.

A discussion / Q&A layer for the community is on the roadmap. See the platform skill for client-side usage.

When to use TVBO

• You want to describe a neural-mass / dynamical-network model once and run it on multiple simulator backends.
• You want your models to be machine-readable, citable, and shareable (the ontology + LinkML schema make this possible).
• You want a structured way to bundle experiments and studies for reproducibility.

Installation

pip install tvbo            # core
pip install tvbo[jax]       # JAX backend
pip install tvbo[tvb]       # The Virtual Brain backend
pip install tvbo[pyrates]   # PyRates backend
pip install tvbo[julia]     # juliacall + Julia backends
pip install tvbo[all]       # everything

Documentation: https://virtual-twin.github.io/tvbo/