Stakeholders' requirements, impact assessment & data sources
The interaction and feedback loop between T1.1 and other subtasks will inform subsequent technical tasks (i.e., T1.2, T1.3 and T1.4) on developing tools using AI and Big Data techniques.
The insights derived from the co-creation task (i.e., T1.1) will provide guidance with other technical tasks regarding data collection, algorithm selection and model validation.
Simultaneously, technical tasks inform co-creation tasks by translating domain knowledge and user requirements into practical features and functionalities, which can be re-evaluated by users and experts for further validation and refinement. This close collaboration between different tasks enables us to develop a user-centric proactive food safety early warning system and eventually contribute to a food system that is more resilient to food safety shocks.
This deliverable describes progress in relation to the derivation of insights from tool users, domain experts, and tool developers on:
- How tools based on AI and Big Data techniques can best help risk assessors and managers ensure food safety in the food supply chain.
- Potential drivers of change related to three supply chains (i.e. chicken, lentils and maize) that should be considered in developing a proactive early digital warning system.
- Prioritizing emerging food safety hazards.
- Identifying relevant data sources and data processing algorithms and validating and improving the performance of emerging risk identification tools.
