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Digital Twins are computational representations of both living and non-living entities and processes, which can be used to analyse and simulate interventions in these entities and processes. When developing Digital Twins, it is important to anticipate on the societal, ethical and safety impacts they may have. Since in the agri-food domain Digital Twins are still in its infancy, it is possible to include societal values from the beginning onwards, during the research and development process. In this paper, we present four themes (i.e. resources, representations, actions and implementations) to organise the anticipation of and reflection on potential impacts of Digital Twins in the agri-food domain. Using insights from the smart farming literature, we assess for each theme which issues and questions require further research and attention, in order to develop an agenda for responsible research and innovation on Digital Twins. [ABSTRACT FROM AUTHOR]

• A conceptual framework is proposed to assess the value of information from Precision Livestock Farming (PLF) technologies. • The difference between the outcome with and without the information renders the value of information. • The value of information combines economic and non-economic considerations of the added value of using PLF technologies. • Ex-ante methods may be useful to design valuable PLF technologies. • Farm advisors could enhance the value of information provided by PLF technologies. Although precision livestock farming (PLF) technologies ensure various dimensions of more precise information, the question arises to what extent additional preciseness provides more value. Literature gives insufficient anchor points to estimate the value of information (VOI) obtained with PLF technologies. This study proposes a conceptual framework with building blocks to determine the VOI. Next, the framework is used to describe factors and existing gaps in the VOI assessment. This, finally, leads to reflections and recommendations about how to assess and improve the VOI of PLF. Literature reveals that the VOI surpasses the mere use of more precise information to take decisions, but encompasses a path from data collection to decisions with particular outcomes. The framework interlinks three building blocks: (i) data processing, (ii) decision making and (iii) impact analysis with factors influencing the VOI such as the process to transform data into information, level of precision, decision rules, social influences, the accuracy of information, herd size and prevalence of the condition measured. Besides profitability, outcomes from decisions include the impact on animal welfare, environment, food safety, and food security. The data-to-value framework allows for a better assessment of VOI and its potentials, and provides anchor points to design useful and valuable PLF technologies. The framework also helps to determine the role of advisors in interpreting the more precise information and in formulating farmer-tailored advice to apply the most optimal practices. Both technology design and advisors' role may enhance the VOI of future PLF developments and applications. [ABSTRACT FROM AUTHOR]