Open Data Schema for Energy

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Semantic Validation

Semantic validation checks whether records are operationally plausible in context, even when they are structurally valid.

Why Semantic Validation Matters

A record can satisfy JSON schema requirements and still be misleading or impossible in practice.

Examples:

Energy values exceeding physical output limits for asset capacity
State/error combinations that conflict with expected operating behavior
Direction/value combinations that are unlikely for the configured asset

Typical Inputs

Semantic checks often require context beyond a single record, such as:

capacity_kw
asset type
recent operating history
expected interval size

Example

from odse import validate

result = validate(
    {
        "timestamp": "2026-02-09T14:00:00Z",
        "kWh": 500.0,
        "error_type": "normal"
    },
    level="semantic",
    capacity_kw=10.0
)

print(result.is_valid)
print(result.warnings)

Output Pattern

errors: hard failures for clearly invalid conditions
warnings: suspicious but potentially explainable conditions

Practical Use

Use semantic validation as a decision-quality gate for forecasting, compliance outputs, and risk analytics.