Many fields of research concern data that carry a spatial or temporal component: data related to a location or time, which often are prone to uncertainty and/or imprecision. As both spatial and temporal data tend to be an additional aspect of the data and as both have similar issues with resolution, relative notions and intuitive notions, they are often considered together. The combination of uncertainty and/or imprecision, an increasing amount of data and the need for a higher level of reasoning on the data requires innovative methods. The first iteration of this event concerns estimating, handling and representing uncertainty within the model, but also new ways of modelling and processing uncertain spatial or temporal data. The main focus is on novel technologies, such as possibilistic and fuzzy methods, to represent, limit or estimate the uncertainty or imprecision; but also on algorithms that involve such methods to process the data accordingly.