MALDI (Matrix-assisted laser desorption/ionization mass spectrometry) imaging mass spectrometry (MALDI MSI) enables the investigation of the spatial distribution of biomolecules and is widely used in systems biology, pharmacology, biomedical research and clinical pathology in recent years. In addition to all the achievements of MALDI MSI, however, as data acquisition increases, it becomes clear that the data generated exhibit a high degree of variability. This includes differences in signal intensity, mass inaccuracies as well as chemical and instrumental background signals. Even data collected under standardized conditions within a laboratory with the same equipment can show significant technical variability. Accordingly, data measured at different locations and with different equipment can only be compared to a very limited extent. So far no suitable algorithms and software tools are available for the detection and quantification of the described effects and therefore the variability often remains unnoticed and thus considerably reduces the data quality. MALDISTAR will therefore address the following objectives: 1. Development of algorithms for the evaluation of quality standards and quantitative metrics 2. Development of mathematical methods for calibration and cross-normalization 3. Development of software tools for the implementation of these methods The project MALDISTAR pursues an open research strategy, involving our large network and the scientific MALDI MSI community.