Visualisation of the (in)accuracy Collection Curation Cookbook to do the survey (quality, completeness, accuracy) As-Built required deliverable - ASCE white paper. Feature naming & structure (Network, Location, time, Semantic) Integration of unstructured data Multiple acquisition methods (radar, lidar, RFID, Survey, …) Innacuracy or lack of data A lot of research to refresh data and collect data Convertion from paper map to digital data Take into account movement of soil ("known") Continuous acquisition Link to common data model Framework/ Fundamental Common Platform, SDI, Centralized Access portal (Discovery, Use, Use Cases Risk Analysis (Insurance Use case) Linked to the use case Linked to uncertainty of data Deep learning for NYC risks. IEEE paper. Fit for purpose (2D, 3D, 4D) Visualisation of the (in)accuracy Visualisation of terrain as important as network Analysis Viz.