Integrated Data Analysis for nuclear fusion

Integrated Data Analysis (IDA) offers a unified way of combining data from different experiments to obtain improved results. IDA meets with typical issues arising in the analysis of data from magnetic confinement fusion experiments. Heterogeneous and complementary experimental data as well as physical prior information are integrated employing Bayesian probability theory. The concept of IDA is compared to the traditional approach for data analysis where sequential analysis and iterative schemes are usually employed. In contrast to classical backward inversion techniques, IDA needs only forward modeling and a thorough error assessment. In practice, the probabilistic description of systematic measurement and model uncertainties are of major importance to resolve data inconsistencies, which is a prerequisite for the integration of different diagnostics results. Complex error propagation is an inherent part of a concise probabilistic one-step analysis.