The mechanical properties obtained with a variety of testing methods (e.g. tensile and fatigue testing, (cyclic) indentation, etc.), microstructural features (e.g. grain size, phase contents, etc.) and physical properties (e.g. electrical conductivity, magnetic permeability, etc.) provide huge opportunities for exploring correlations. Interactive visual data exploration and topological data analysis are promising to find and evaluate correlations within materials datasets. The major challenges for data analysis are the lack of standardization on the data input, the lack of helpful guidelines for applying existing data analysis/visualization packages, and the complex nature of the data that is commonly not directly supported by these libraries. To address these challenges, the following support is required: (i) Standard data formats have to be defined and described by an ontology and the transformation from arbitrary data to this format has to be elaborated. (ii) Correlation analysis techniques need to be revisited and systematized along. (iii) Best practices need to be defined and tested as well as augmented with novel analysis techniques.