Big Data Visualisation in the Maritime Industry

VesselAI aims to develop, validate and demonstrate a unique framework to unlock the potential of extreme-scale data and advanced HPC, AI and Digital Twin technologies in the maritime industry. With the growth of data and the digitalization of the sector comes the need to process and visualise this information as the maritime industry generates and consumes huge amounts of different types of data every day. This paper presents literature review focusing on two aspects: (1) an examination of visualization tools available, and (2) an investigation into existing works and studies within the domain of Big Data visualization. This study addresses specific visualization requirements pertinent to the Maritime domain, including the necessity for intricate spatial-temporal visualizations encompassing diverse datasets such as weather patterns, vessel trajectories, and Automatic Identification System (AIS) data. VesselAI intends to build the VesselAI Visualisation and Reporting Engine to empower maritime users and stakeholders to make informed decisions and gather knowledge from data. To this end a platform based on Apache Superset was applied and tested in response to challenges faced by maritime stakeholders and the findings indicate that Apache Superset's robust capabilities, including a vast number of visualisation types supported, out-of-the-box data connectors, customization options, and security features, effectively met the requirements identified in the literature and by pilot users.