Understanding the Data Model & Provenance Ontology
Learn how TARE connects execution, telemetry, evidence, and graph data structures for reviewable records.
TARE provides custody-aware records for modern laboratories. The platform uses a unified Provenance Ontology to connect record lifecycle context.
Unlike software systems that leave records in flat, disconnected tables, TARE organizes lab context into four interconnected pillars. This structure helps reviewers follow actions, readings, and resulting artifacts back to their recorded source context.
1. Execution
Represents the intentional actions taken by human operators and configured workflows. This includes top-level Runs (often tied to Experiments) and granular Process Steps.
2. Telemetry
Captures the passive or automated signals generated during operations. Events track state changes, while Observations log subjective or objective streams from sensors.
3. Evidence
The tangible outputs of the workflow. Artifacts represent physical or digital objects produced, while Derived Results are analysis outputs that stay tied to source context.
4. Graph
The relationship layer for the record. Using Provenance Edges, TARE links record elements with hash context for later review.
Projects, Experiments, and Cases
On top of this low-level ontology, TARE surfaces human-readable organizational layers:
Projects
The primary container for work over time (e.g., a grant or client program).
Experiments
An R&D study tracked through a status lifecycle (planned → in progress → completed).
Cases
An investigation or work order requiring strict evidence tracking.