Atom probe tomography (APT) constitutes a rather unique analytical technique for the 3D elemental characterization of solid materials with potentially sub-nm spatial resolution. APT is, therefore, very well suited for the analysis of a nanostructured specimen such as matrix-embedded nanoparticles, ultra-thin films and junctions, grain boundaries, and others. This presentation will emphasize these capabilities, describing three methods of data mining that can be used to fully exploit APT: (i) Visualization of atomic lattice planes in crystalline specimens, (ii) the determination of iso-concentration surfaces and proximity histograms derived thereof, and (iii) a cluster identification algorithm based on maximum-atom separations. These approaches will be illustrated by means of different types of samples: a crystalline tungsten specimen, a Fe/Cr/Fe multilayer system, Si nanocrystals embedded in a silicon oxide matrix, and Mg clustering in GaN. The results demonstrate clearly that sub-nm-sized structures can be characterized by APT. Copyright © 2014 John Wiley & Sons, Ltd.