CNRS - Centre National de Recherche Scientifique (CNRS)
Contributions in WP2
Contributing 3PM to:
T2.3: Improve the technological readiness of key datasets
Lead: UOY (5PM).
Effort by contributors: NILU (5PM), CNRS (3PM), DDS (3PM), ZHAW (3PM), ULEI (2PM), SEI (2PM), ETHZ (2PM), COOL (2PM). Timing: M22-34. To enhance uptake, we will develop recommendations for each tool/data provider based on the assessment of weaknesses and best practice examples (T2.2). We will actively disseminate findings to data providers, who will be invited to attend one-to-one discussion meetings with the project team. We will also host two workshops across multiple partners (covering the same topic, but split to allow attendance from more parties and deeper interaction) to encourage further sharing of best practice and ‘challenges’ in responding to recommendations. An academic publication will also be produced to share outcomes openly. For tools provided by project partners we will, via project funding, implement selected recommendations. This task contributes to D2.2 (M24), D2.3 (M32) and D2.4 (M34). Milestone: M2.2 (M28) Stakeholder workshops (M28); M2.3 (M28): Assessment of which internal tool/data provider recommendations will be implemented (M28). Contributes to:
D2.2 (M24), D2.3 (M32), D2.4 (M34).
This task is linked to the following milestones: MS2.2 (M28), MS2.3 (M28).
Contributing 1PM to:
T2.5: Launch an AI conversational agent (AICA) for food LCA supply chain and environmental impact info
Lead: INTEC (24PM).
Effort by contributors: ARBO (22PM), UOY (2PM), SEI (2PM), NILU (1PM), ULEI (1PM), ETHZ (1PM), CNRS (1PM), DDS (1PM). Timing: M26-46. We will develop a prototype AICA that answers user-posed questions in natural language about the impacts of the EU’s food system. It will utilise food linked LCA, footprint and other data developed within and outwith the project (incl. sources developed in WP1 and assessed in WP2), collated into a central structured database. Quantitative data will be complemented by information derived from research outputs (including outputs from WP3 and WP4) and other assessments. Training of the AICI will take place via development of common questions inspired by the EU’s policy context and the guidance received via stakeholders (WP5). We will undergo a thorough validation process, drawing on expertise from across the consortium. Iteration of the model based on feedback from the experts will take place before final production launch towards the end of the project. Contributes to:
D2.6 (M42), D2.7 (M42).
This task is linked to the following milestones: MS2.4 (M30), MS2.5 (M32), MS2.6 (M34).