Data Sharing Networks for Food Risk Prevention
Data Sharing Networks are
trusted, topic-specific collaboration environments
where multiple organisations contribute data under shared governance rules
in order to generate aggregated, anonymised insights.
Instead of exchanging raw datasets,
participants contribute data that is harmonised, anonymised, and analysed collectively,
enabling early detection of emerging risks that cannot be identified by individual organisations alone.
Why Data Sharing Networks Matter
Food safety and microbiological risks are fragmented across companies, geographies, and testing regimes.
Individual organisations only see partial signals, limiting their ability to detect emerging risks early.
Traditional data sharing approaches fail because companies are unwilling to expose sensitive or proprietary data.
EFRA Data Sharing Networks address this challenge by enabling collaboration focused on collective intelligence, not raw data exchange.
How EFRA Enables Secure & Governed Data Sharing
Key Capabilities
Semantic harmonisation of heterogeneous datasets
Aggregation and anonymisation by design
Privacy-preserving analytics
Network-level access control
Aggregated analytics delivery (important revision)
Aggregated analytics and insights generated through EFRA technologies are presented to participants via FOODAKAI,
the risk intelligence platform enhanced by EFRA.
FOODAKAI acts as the operational interface where authorised members of each Data Sharing Network
can explore dashboards, trends, and indicators derived from anonymised, pooled data.
🏆 Validated EFRA Use Case:
Food Microbiology Intelligence Network (F-MIN)
The Food Microbiology Intelligence Network (F-MIN) is a pilot Data Sharing Network that demonstrates
how EFRA tools can be used to securely share and co-analyse microbiological testing data across food companies.