Documentation Index
Fetch the complete documentation index at: https://docs.mangrovesystems.com/llms.txt
Use this file to discover all available pages before exploring further.
What you’ll learn in this lesson:
- Decide when to add new event types vs. extend existing ones
- Connect multiple event types in a single model
- Handle unit conversions and standardization
- Build validation checks that prevent bad data propagation
When to create a new event type
Not every piece of data needs its own event type. Use these guidelines to decide:- Create a new event type when...
- Extend an existing event type when...
- The data comes from a different operational activity (e.g., receiving feedstock vs. delivering biochar)
- The data has a different cadence (e.g., lab tests happen weekly, deliveries happen daily)
- The data has a different source (e.g., weighbridge system vs. lab instrument)
- The data needs separate evidence (e.g., a delivery ticket vs. a lab certificate)
New event types for Mangrove Biochar
To build a complete carbon accounting model, Mangrove Biochar needs at least two additional event types beyond Biochar Delivery:Feedstock Receipt
Captures raw material entering the system.
| Datapoint | Value Type |
|---|---|
| Feedstock type | text |
| Wet mass (tonnes) | number |
| Moisture content (%) | number |
| Receipt date | date |
| Supplier ID | text |
Lab Analysis
Captures lab test results for biochar quality.
| Datapoint | Value Type |
|---|---|
| Sample ID | text |
| Carbon content (%) | number |
| H:C molar ratio | number |
| Ash content (%) | number |
| Analysis date | date |
Connecting multiple event types in a model
A single model can reference datapoints from any event type in the project. The model’s input nodes specify which datapoint slug to pull from — Mangrove matches them to events within the accounting period.Event matching: When generating batches, Mangrove pulls datapoints from events whose date range falls within the accounting period. If a model references datapoints from multiple event types, all referenced events must exist for that period — otherwise validation will flag missing data.
Unit conversions and standardization
Different event types may record values in different units. Your model must handle conversions explicitly. Common conversions in carbon accounting:| From | To | Conversion |
|---|---|---|
| Wet mass (tonnes) | Dry mass (tonnes) | wet_mass × (1 - moisture/100) |
| Carbon content (%) | Carbon fraction | carbon_pct / 100 |
| Carbon mass (tonnes C) | CO2 equivalent (tCO2e) | carbon_mass × 3.67 |
| Distance (miles) | Distance (km) | miles × 1.609 |
Building validation checks
Bad data in → bad results out. Validation helps catch problems before they propagate through calculations.What to validate
- Range checks — Is the value within a reasonable range? (e.g., moisture content between 0-100%)
- Presence checks — Are all required datapoints present for the accounting period?
- Consistency checks — Do related values make sense together? (e.g., dry mass should be less than wet mass)
Where validation happens
At data entry
When adding events, Mangrove validates required fields and data types. Configure datapoints as required in the event type to enforce this.
In the model
Use Keisan expressions to add runtime validation — for example, flagging negative values or out-of-range inputs. The model’s test Console helps you verify these.
At batch generation
When you generate batches, Mangrove validates that all required datapoints are present. Missing data shows as validation messages you must resolve before submitting.
Check your understanding
When should you create a new event type instead of adding a datapoint to an existing one?
When should you create a new event type instead of adding a datapoint to an existing one?
Create a new event type when the data comes from a different operational activity, has a different cadence, comes from a different source, or needs separate evidence. Extend an existing event type when the data is captured at the same time and comes from the same operational step.
What role do static inputs play in models?
What role do static inputs play in models?
Static inputs are values that don’t change from batch to batch — emission factors, conversion constants, or methodology-defined parameters. They come from the project’s resource libraryand are referenced by model nodes just like event datapoints. Unlike constants hardcoded in the model, static inputs can be updated without modifying the model itself.
How does Mangrove handle data from multiple event types in a single model?
How does Mangrove handle data from multiple event types in a single model?
A model can reference datapoints from any event type in the project using the datapoint’s slug. When generating batches, Mangrove pulls values from all events whose date range falls within the accounting period. If a referenced datapoint is missing for the period, validation will flag it before batch submission.
You’re now ready to put this into practice in the Module 2 Exercise: Build a Multi-Step Calculation Pipeline.