Case Study: WRAP
WRAP Food Loss and Waste Data Taxonomy
Commissioned by WRAP (procurement reference PRC228) to turn the international Food Loss and Waste Standard into structured, machine-readable data infrastructure for its Food Programme and global Food Pact Network.
Entity groups
5
coded classification dimensions
Coded entities
84
SKOS concepts across five dimensions
Reach
~200
UK Food and Drink Pact organisations
The Challenge
WRAP's UK Food and Drink Pact (formerly the Courtauld Commitment 2030) asks the UK food industry to halve food waste by 2030 (UN Sustainable Development Goal 12.3), uniting nearly 200 organisations across the supply chain. Together with the wider international network of food pacts, signatories report their food loss and waste data using locally divergent definitions, product groupings and destination categories. Without a shared, coded classification system this data cannot be reliably aggregated or compared, quietly undermining the ability to measure collective progress against the headline target.
WRAP needed the conceptual Food Loss and Waste Accounting and Reporting Standard translated into implementable, machine-readable data infrastructure that could be used consistently across countries and reporting tools while remaining platform-agnostic.
What We Delivered
We built the taxonomy as working data infrastructure, not a static reference document: five entity groups with hierarchical classifications, controlled vocabularies and unique codes (84 coded entities, 680 RDF triples), expressed as a machine-readable SKOS and JSON-LD schema with structural coverage validation and version-controlled change governance. Machine-checkable SHACL validation shapes and FoodEx2 mappings are scaffolded for Phase 2.
| # | Entity group | Coverage |
|---|---|---|
| 1 | Product Category | Hierarchical food product classes (e.g. bakery, dairy, fruit and vegetables) with unique codes. |
| 2 | Supply Chain Stage | Primary production, manufacturing, retail, hospitality and household stages. |
| 3 | Waste Destination | Aligned to the Food Loss and Waste Standard destination categories. |
| 4 | Intervention Type | Coded prevention and redistribution actions for consistent intervention tracking. |
| 5 | Food Waste Hierarchy | Prevention through to disposal, ranked for comparable reporting. |
The schema is interoperable with the reference food ontologies FoodOn and EFSA FoodEx2, and the validation rules reject malformed or inconsistent records before they corrupt aggregation. Delivered through iterative co-design with WRAP subject-matter experts.
Outcome
A publishable, machine-readable taxonomy that lets the Food Pact Network classify and compare food waste data on a like-for-like basis. It is grounded in the international Food Loss and Waste Accounting and Reporting Standard, the WRAP Data Capture Sheet and Codex GSFA, positioning Tesseract Academy not just as users of data standards but as builders of the infrastructure that implements them.
"Unlike consultancies that design taxonomies as static reference documents, we build structured classification systems as working data infrastructure, with machine-readable schemas, validation rules and hierarchical codes that can be implemented directly in reporting tools."
Dr Stylianos Kampakis, Managing Director, Tesseract Academy
Related open-source work
See our open wastewater data-quality case study, which re-points the same validation approach onto environmental monitoring data.
