Abstract: A method for predicting a spatial location of a real-world phenomenon at a future time comprises: (a) receiving dependent variable data for one or more dependent variables associated with the phenomenon from an observation source, the dependent variable data being time stamped and including a geographical reference; (b) responsive to receiving the dependent variable data, collating the dependent variable data with independent variable data for one or more independent variables associated with the geographical reference and storing the collated data in a data store; (c) receiving a prediction request for predicting the spatial location of the real-world phenomenon at the future time; (d) retrieving collated data that satisfy a predefined relevance criterion; and (e) implementing an algorithm that utilises or is derived from the retrieved collated data and predicting the spatial location of the real-world phenomenon based on the output of the algorithm.