“If we cannot measure it, it does not exist” is a frequently used statement in science paraphrasing the importance of instrumentation and measurements to almost all fields of science. By improving a measurement, we can better understand the underlying phenomena and it makes instrumentation and measurement so exciting, that single improvements e.g. with respect to measurement methodologies, systems for instrumentation and measurement, or novel sensors can have dramatically impact on the work of many other scientists.

The availability of network technology, miniaturized nodes and sensors, as well as of computers to process huge amounts of data have given rise to new research areas standing behind buzz words like big data, the internet of things or industry 4.0 and autonomous systems. With the huge amount of data available, the question arises whether predictions made from a high number of highly uncertain measurements will produce usable or trustable results. This is of particular interest for autonomous systems, i.e. systems where correctness of predictions can mean the difference between life and death.