Throughout the food supply chain, between production, transportation, packaging, and green employment, a plethora of indicators cover the environmental footprint and resource use. By defining and tracking the more inefficient practices of the food supply chain and their effects, we can better understand how to improve agricultural performance, track nutrition values, and focus on the reduction of a major risk to the environment while contributing to food security. Our aim is to propose a framework for a food supply chain, devoted to the vision of zero waste and zero emissions, and at the same time, fulfilling the broad commitment on inclusive green economy within the climate action. To set the groundwork for a smart city solution which achieves this vision, main indicators and evaluation frameworks are introduced, followed by the drill down into most crucial problems, both globally and locally, in a case study in north Italy. Methane is on the rise in the climate agenda, and specifically in Italy emission mitigation is difficult to achieve in the farming sector. Accordingly, going from the generic frameworks towards a federation deployment, we provide the reasoning for a cost-effective use case in the domain of food, to create a valuable digital twin. A Bayesian approach to assess use cases and select preferred scenarios is proposed, realizing the potential of the digital twin flexibility with FAIR data, while understanding and acting to achieve environmental and social goals, i.e., coping uncertainties, and combining green employment and food security. The proposed framework can be adjusted to organizational, financial, and political considerations in different locations worldwide, rethinking the value of information in the context of FAIR data in digital twins.

翻译：在食品供应链中，从生产、运输、包装到绿色就业，大量指标覆盖了环境足迹和资源使用。通过定义并追踪食品供应链中效率较低的做法及其影响，我们能够更好地理解如何提升农业绩效、追踪营养值，并在为粮食安全做出贡献的同时聚焦于减少环境重大风险。我们的目标是提出一个致力于零浪费和零排放愿景的食品供应链框架，同时履行气候行动中关于包容性绿色经济的广泛承诺。为奠定实现这一愿景的智慧城市解决方案基础，我们介绍了主要指标和评估框架，随后以北意大利的案例研究深入探讨全球和本地最关键的问题。甲烷在气候议程中的重要性日益上升，特别是在意大利农业部门难以实现减排目标。因此，从通用框架走向联合部署，我们提供了在食品领域构建具有成本效益的用例的理由，以创建有价值的数字孪生。我们提出了一种贝叶斯方法来评估用例并选择优选方案，从而利用FAIR数据实现数字孪生灵活性的潜力，同时理解和采取行动实现环境与社会目标，即应对不确定性、将绿色就业与粮食安全相结合。所提出的框架可根据全球不同地点的组织、财务和政治考量进行调整，重新思考数字孪生中FAIR数据背景下的信息价值。