The rapid evolution of digital technology and designed intelligence, such as the Internet of Things (IoT), Big data analytics, Artificial Intelligence (AI), Cyber Physical Systems (CPS), has been a catalyst for the 4th industrial revolution (known as industry 4.0). Among other, the two key state-of-the-art concepts in Industry 4.0, are Industrial IoT (IIoT) and digital twins. IIoT facilitates real-time data acquisition, processing and analytics over large amount of sensor data streams produced by sensors installed within a smart factory, while the ‘digital twin’ concept aims to enable smart factories via the digital replication or representation of physical machines, processes, people in cyber-space. This paper explores the capability of present-state open-source platforms to collectively achieve digital twin capabilities, including IoT real-time data acquisition, virtual representation, analytics, and visualisation. The aim of this work is to ‘close the gap’ between research and implementation, through a collective open source IoT and Digital Twin architecture. The performance of the open-source architecture in this work, is demonstrated in a use-case utilising industry ‘open data’, and is bench-marked with universal testing tools.