This article applies a knowledge graph-based approach to unify multiple heterogeneous domains inherent in climate and energy supply research. Existing approaches that rely on bespoke models with spreadsheet-type inputs are noninterpretable, static and make it difficult to combine existing domain specific models. The difficulties inherent to this approach become increasingly prevalent as energy supply models gain complexity while society pursues a net-zero future. In this work, we develop new ontologies to extend the World Avatar knowledge graph to represent gas grids, gas consumption statistics, and climate data. Using a combination of the new and existing ontologies we construct a Universal Digital Twin that integrates data describing the systems of interest and specifies respective links between domains. We represent the UK gas transmission system, and HadUK-Grid climate data set as linked data for the first time, formally associating the data with the statistical output areas used to report governmental administrative data throughout the UK. We demonstrate how computational agents contained within the World Avatar can operate on the knowledge graph, incorporating live feeds of data such as instantaneous gas flow rates, as well as parsing information into interpretable forms such as interactive visualizations. Through this approach, we enable a dynamic, interpretable, modular, and cross-domain representation of the UK that enables domain specific experts to contribute toward a national-scale digital twin.

The objectives of this study were to examine heat stress conditions at cow level and to investigate the relationship to the climate conditions at 5 different stationary locations inside a dairy barn. In addition, we compared the climate conditions at cow level between primiparous and multiparous cows for a period of 1 week after regrouping. The temperature-humidity index (THI) differed significantly between all stationary loggers. The lowest THI was measured at the window logger in the experimental stall and the highest THI was measured at the central logger in the experimental stall. The THI at the mobile cow loggers was 2·33 THI points higher than at the stationary loggers. Furthermore, the mean daily THI was higher at the mobile cow loggers than at the stationary loggers on all experimental days. The THI in the experimental pen was 0·44 THI points lower when the experimental cow group was located inside the milking parlour. The THI measured at the mobile cow loggers was 1·63 THI points higher when the experimental cow group was located inside the milking parlour. However, there was no significant difference for all climate variables between primiparous and multiparous cows. These results indicate, there is a wide range of climate conditions inside a dairy barn and especially areas with a great distance to a fresh air supply have an increased risk for the occurrence of heat stress conditions. Furthermore, the heat stress conditions are even higher at cow level and cows not only influence their climatic environment, but also generate microclimates within different locations inside the barn. Therefore climate conditions should be obtained at cow level to evaluate the heat stress conditions that dairy cows are actually exposed to.