Data points
The activity data Darwin handles, its value-chain position, and how heterogeneous data is reconciled.
What activity data do we use?
Data points carry the activity data attached to organisation units and sites. We handle 4 main types:
- Financial data: turnover, sales or procurement data, expressed in a currency.
- Product data: transformed materials & goods, measured in weight or volume metrics.
- Commodity data: subset of product data — raw materials that are standardized and tradable (e.g. wheat, steel), measured in weight or volume metrics.
- Pressures data: factors driving biodiversity loss (e.g. land use, pollution, climate change), measured in physical flows (e.g. m³ water, km²).
Site location data is handled as part of the Organisation entity model rather than as an activity data type — it positions the organisation in space rather than describing an activity.
Data type & precision
The type of data provided affects the precision of the assessment:
| Data type | Quality | Precision |
|---|---|---|
| Pressures | A | Highest — measurable physical flows |
| Commodity | B | High — specific raw materials |
| Product | C | Medium — product-level averages |
| Financial | D | Lower — sector averages |
The further up this table a data point sits, the closer the assessment is to measured physical reality; the further down, the more it relies on sector averages. A data quality score reflects the precision of the input data actually used.
What value chain do we cover?
Our value chain coverage follows the standard scope framework used in climate and corporate sustainability reporting:
- Scope 1 — Direct operations: pressures and activities from assets directly owned or controlled by the organisation.
- Scope 2 — Indirect energy: purchased energy and utilities consumed by the organisation.
- Scope 3 — Full value chain:
- Upstream: suppliers, raw material sourcing, purchased goods and services.
- Downstream: product use, distribution, customers, end-of-life.
For nature-related assessments, isolating Scope 2 as a standalone scope is less methodologically relevant than in climate accounting: the nature impacts of purchased energy are best captured through the upstream supply chain of energy suppliers. In Darwin, Scope 2 is therefore included within Scope 3 upstream, ensuring complete value chain coverage without double-counting.
We accept input data across all scopes, enabling nature-related risk and impact assessments from a company's direct operations to its full upstream supply chain and downstream distribution network.
How scopes are assigned
Scopes are not set on the data point directly — they follow from the value-chain position of the organisation unit that carries the data. The root entity and sites are always Scope 1 (own operations); other entities inherit the upstream or downstream position assigned to them. This is what lets the same activity contribute to the correct company-level scope during consolidation.
How do we manage heterogeneous data?
One of the main challenges users face is managing varying data granularity across internal entities. We address this with a proprietary algorithm that:
- handles multiple data input types, ensuring consistency across different levels (entities, scope).
- automatically propagates relevant data across entities where possible, enhancing overall data quality (with some manual adjustments required for conflict resolution).
This approach ensures that biodiversity assessments in Darwin remain accurate, prevent double counting, and align with real-world business structures. It also gives users control over data usage and refinement, improving the precision of biodiversity footprint calculations.