The concept of the Digital Twin has emerged as a key enabler of Industrial Internet applications, radically simplifying creation, deployment and management of Industrial IoT (IIoT) solutions. Digital Twins are dynamic digital representations that enable companies to understand, predict and optimize the performance of their machines and their business. Twins model the structure, behavior and context of a physical industrial asset. They assemble information from OT and IT data sources into a Twin model and use a combination of physics- and machine learning-based analytics to extract business relevant insights and to continuously improve the Twin model. IIoT Platforms bring Digital Twins to life – they provide execution and management capabilities for elements of the Twin (e.g., analytics, semantic models, learning) in the edge-to-cloud fog compute topologies typical for industrial internet applications. The session will introduce key concepts of Digital Twins and describe typical use cases. It will explore challenges in operationalizing Twins in edge-2-cloud fog computing environments and discuss the role of the OpenFog Reference Architecture in addressing those challenges. "