Prognostics and health management enables predictive maintenance through techniques like data analytics. Railway catenary is categorised as a linear asset, where inspection and maintenance present challenges due to large distribution of the asset and limitation of current methods. Digital twin can be used to support system level analytics from design to decommissioning. Development of digital twin for railway catenary requires data analytics as well as strategy for information and knowledge storage. Point cloud data recovered through LiDAR scanning contains spatial information, Point cloud data analytics and representation of extracted information forms the base for development of railway catenary digital twin.