The mechanisms governing materials can be highly intricate and the relevant descriptive parameters to describe a certain materials' property are often unknown. Thus, one would like to offer many possibly relevant candidate parameters and let the SGD analysis identify the key ones. However, optimizing the quality function is a combinatorial problem with respect to the number of descriptive parameters and efficient search algorithms are therefore crucial. Advances in Science and Technology to Meet Challenges In order to address some of these open questions, we approach the SGD as a multi-objective-optimization problem for the systematic identification of SG rules that correspond to a multitude of generalityexceptionality trade-offs. optimal SGD solutions with respect to the objectives coverage and utility function, as illustrated for the example of identification of perovskites with high bulk moduli in Fig. . Once the coherent collections of SG rules are identified, the overlap between SG elements can be used to assess their similarity. A high similarity between SG rules might indicate that the rules are redundant. Thus, the similarity analysis can be used to choose the SG rules that should be considered for further investigation or exploitation. , respectively), the electron affinity and ionization potential of isolated B species (𝐸𝐴 𝐵 and 𝐼𝑃 𝐵 , respectively), the expected oxidation state of A (𝑛 𝐴 ), the equilibrium lattice constant (𝑎 0 ), and the cohesive energy (𝐸 0 ).