Multisensor data fusion in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from one or more sensors. The theoretical background originates in classical mathematics and statistics, in methods of artificial intelligence (AI) and in the Bayesian fusion approach. Sensor technologies and sensor characteristics influence the data fusion process and determine the gain of information compared to the application of a single sensor. Homogeneous and inhomogeneous sensor configurations lead to complementary, competitive and cooperative information integration with specific advantages depending on the application. The scope includes image fusion, tactile and optical coordinate metrology, coherent and incoherent optical measuring techniques, computed tomography as well as scanning probe microscopes.