1 ) A method for identifying data patterns from data comprising at least one data object, said data having at least one existing pattern class associated therewith, said data object being represented by a base feature vector, at least one of said base feature vectors having a structure of higher-level and lower-level feature vectors such that at least one element of a higher-level feature vector is a lower-level feature vector; said method comprising steps of: (a) deriving a pattern class prototype in respect of the or each existing pattern class; (b) creating a new pattern class in respect of a data object; and (c) deriving a pattern class prototype in respect of said new pattern class, for the or each of said existing pattern classes: (d 1 ) determining, in respect of elements of a higher-level feature vector, an Element Similarity Measure indicative of a measure of similarity between elements of one or more lower-level feature vectors thereof and corresponding elements of a pattern class prototype of said existing pattern class; and (d 2 ) determining, in dependence on said Element Similarity Measures, a Vector Similarity Measure indicative of a measure of similarity between said higher-level feature vector and a corresponding vector of a pattern class prototype of said existing pattern class; (e) determining, in dependence on Vector Similarity Measures determined in respect of each of said existing pattern classes and according to predetermined criteria, whether or not said data object is a member of one of said existing pattern classes; (f 1 ) in the event of a determination that said data object is a member of an existing pattern class, adding said data object to a set of members of said existing pattern class; (f 2 ) in the event of a determination that said data object is not a member of an existing pattern class, generating a new pattern class and adding said data object to a set of members of said new pattern class; and (g) identifying any new pattern class so generated to be indicative of a new data pattern.