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Informing and engaging citizens to adopt sustainable diets is a key strategy for reducing global environmental impacts of the agricultural and food sectors. In this respect, the first requisite to support citizens and actors of the food sector is to provide them a publicly available, reliable and ready to use synthesis of environmental pressures associated to food commodities. Here we introduce the SU-EATABLE LIFE database, a multilevel database of carbon (CF) and water (WF) footprint values of food commodities, based on a standardized methodology to extract information and assign optimal footprint values and uncertainties to food items, starting from peer-reviewed articles and grey literature. The database and its innovative methodological framework for uncertainty treatment and data quality assurance provides a solid basis for evaluating the impact of dietary shifts on global environmental policies, including climate mitigation through greenhouse gas emission reductions. The database ensures repeatability and further expansion, providing a reliable science-based tool for managers and researcher in the food sector.

Geo-localized, mobile applications can simplify a tourist visit, making the relevant Point of Interests more easily and promptly discernible to users. At the same time, such solutions must avoid creating unfitting or rigid user profiles that impoverish the users' options instead of refining them. Currently, user profiles in recommender systems rely on dimensions whose relevance to the user is more often presumed than empirically defined. To avoid this drawback, we build our recommendation system in a two-step process, where profile parameters are evaluated preliminarily and separately from the recommendations themselves. We describe this two-step evaluation process including an initial survey (N = 206), and a subsequent controlled study (N = 24). We conclude by emphasizing the benefit and generalizability of the approac

This study focuses on social feedback, namely on information on the outcome of users' online activity indirectly generated by other users, and investigates in a real setting whether it can affect subsequent activity and, if so, whether participants are aware of that. SkyPas, an application that calculates, transmits, and displays social feedback, was embedded in a common instant messaging service (Skype(™)) and used during a 7-week trial by 24 office workers at a large business organization. The trial followed an ABA scheme in which the B phase was the feedback provision phase. Results show that social feedback affects users' communication activity (participation, inward communication, outward communication, and reciprocity), sometimes even after the feedback provision phase. At the same time, users were poorly aware of this effect, showing a discrepancy between self-reported and observational measures. These results are then discussed in terms of design transparency and task compatibility.