1. A system comprising: a knowledge management component to acquire, classify and disseminate information of a dataset; a human-computer interaction component to visualize multiple perspectives of the dataset and to model user interactions with the multiple perspectives; and an adaptivity component to modify one or more of the multiple perspectives of the dataset based on a user-interaction model; wherein the human-computer interaction component comprises at least one hardware processor and memory configured to: (I) place data elements from a dataset, associated with separate ontologies, into an N dimensional information space based on ontological structure and semantic similarity among ontology elements, and (II) reduce the N dimensional information space based on a received perspective definition for visualization; wherein the placement of the data elements comprises, for a given ontology of the separate ontologies and a given parent node C p in the given ontology with child nodes {C 1 , C 2 ,. .. , C x }, and letting S={S 1 , S 2 ,. .. , S x , S p } where S i denotes documents that are assigned to concept C i : (I) calculate term importance values for each term in the documents S to generate a set T={T 1 , T 2 ,. .. , T x , T p } where T i denotes a set of K terms that have highest term importance values, (II) issue search queries to retrieve results R={R 1 , R 2 ,. .. , R x , R p } where R i denotes documents returned from the search query with terms T i , (III) estimate co-relation between (C p , C i ), where i=1. .. x, according to Cover(C p , C i )=|R p ∩R i ∥R p |≈P[C i |C p ], where Cover is the conditional probability of C i given C p , and (IV) calculate distance between two concepts C x and C y based on Sim(C x , C y )=2*P/P x +P y +2*P r , where C r is the least common super-concept between C x and C y , P x is the length of path from C x to C r , P y is the length of path from C y to C r , and P r is the length of path from C r to the root node; and wherein the reduction of the N dimensional information space comprises projecting into a three dimensional vector space, having bases α 1 , α 2 , α 3 , in accordance with α 1 =T 1 ({β 1 , β 2 ,. .. , β N })=β 1 , α 2 =T 2 ({β 1 , β 2 ,. .. , β N })=β 2 , and α 3 =T 3 ({β 1 , β 2 ,. .. , β N })=β 3 , where T 1 , T 2 , T 3 are each a linear or nonlinear combination of the N bases in the N dimensional information space, and β 1 , β 2 , β 3 are bases for the three retained dimensions.