The paper "Digital Twin: Values, Challenges and Enablers" by Adil Rasheed, Omer San, and Trond Kvamsdal explores the concept of digital twins, which are adaptive models of complex physical systems. The authors review recent advancements in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, and data processing tools, highlighting their impact on society. Digital twins are described as computational megamodels, device shadows, mirrored systems, avatars, or synchronized virtual prototypes, and they play a transformative role in designing and operating cyber-physical intelligent systems. The paper identifies eight key values of digital twins, including real-time remote monitoring and control, greater efficiency and safety, predictive maintenance and scheduling, scenario and risk assessment, improved team synergy and collaboration, more efficient decision support, personalized products and services, and better documentation and communication. It also discusses diverse applications of digital twins in health, meteorology, manufacturing, education, cities, transportation, and energy sectors. Common challenges in implementing digital twins include data security and management, data quality improvements, latency, real-time simulations, large-scale data fusion, intelligent data analytics, predictive capacity, transparency, and generalization across different application areas. The paper outlines enabling technologies such as physics-based modeling, data-driven modeling, big data cybernetics, infrastructure and platforms, and human-machine interfaces to address these challenges. Physics-based modeling involves experimental and numerical approaches, while data-driven modeling leverages machine learning and artificial intelligence to handle large datasets. Big data cybernetics combines physics-based models with data-driven methods to improve system steering and control. The paper concludes with recommendations for stakeholders in various industries, emphasizing the need for collaboration and innovation to fully realize the potential of digital twins.The paper "Digital Twin: Values, Challenges and Enablers" by Adil Rasheed, Omer San, and Trond Kvamsdal explores the concept of digital twins, which are adaptive models of complex physical systems. The authors review recent advancements in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, and data processing tools, highlighting their impact on society. Digital twins are described as computational megamodels, device shadows, mirrored systems, avatars, or synchronized virtual prototypes, and they play a transformative role in designing and operating cyber-physical intelligent systems. The paper identifies eight key values of digital twins, including real-time remote monitoring and control, greater efficiency and safety, predictive maintenance and scheduling, scenario and risk assessment, improved team synergy and collaboration, more efficient decision support, personalized products and services, and better documentation and communication. It also discusses diverse applications of digital twins in health, meteorology, manufacturing, education, cities, transportation, and energy sectors. Common challenges in implementing digital twins include data security and management, data quality improvements, latency, real-time simulations, large-scale data fusion, intelligent data analytics, predictive capacity, transparency, and generalization across different application areas. The paper outlines enabling technologies such as physics-based modeling, data-driven modeling, big data cybernetics, infrastructure and platforms, and human-machine interfaces to address these challenges. Physics-based modeling involves experimental and numerical approaches, while data-driven modeling leverages machine learning and artificial intelligence to handle large datasets. Big data cybernetics combines physics-based models with data-driven methods to improve system steering and control. The paper concludes with recommendations for stakeholders in various industries, emphasizing the need for collaboration and innovation to fully realize the potential of digital twins.