1. A method for generating a visual summary of non-visual data, said method comprising: obtaining said non-visual data; obtaining metadata describing one or more data types in said obtained non-visual data suitable for a visual summary of said non-visual data, wherein said obtaining metadata comprises: detecting one or more items of metadata in the non-visual data that correspond to one or more items of metadata present in at least one established mapping between metadata and one or more visual summary requirements of at least one given visualization type; and estimating a measure of accuracy between the one or more detected items of metadata and the one or more items of metadata present in the at least one established mapping; selecting multiple visual metaphors for said obtained non-visual data based on said metadata and said measure of accuracy, wherein each of said multiple visual metaphors comprises a stored visual representation, and wherein said selecting comprises selecting, for each of one or more sub-sets of the non-visual data, the stored visual representation having the highest similarity measure in connection with a set of characteristics of the sub-set of the non-visual data derived from said metadata; generating said visual summary of said non-visual data by instantiating a combination of said multiple selected visual metaphors; instantiating said visual summary to allow a user to interact with said visual summary, wherein said instantiating comprises adjusting an appearance of an annotated version of said obtained non-visual data associated with a mapping confidence value below a predefined threshold, wherein said mapping confidence value estimates a confidence of said annotated version; and mapping one or more values of the obtained non-visual data to values supported by a visualization, wherein said mapping comprises calculating a semantic distance between (i) one or more values of an annotated version of the obtained non-visual data and (ii) one or more values supported by one or more visualization examples based on a statistical calculation of co-occurrence of value pairs.