The complexity of data in catalysis arises from several sources:
Multidimensionality: Data often spans multiple dimensions, including time, temperature, pressure, and concentration, complicating analysis. Heterogeneity: Catalytic systems can involve diverse materials, phases, and interfaces, leading to complex datasets that are difficult to standardize. Interdisciplinary nature: Catalysis research integrates chemistry, physics, materials science, and engineering, each contributing unique data types and analytical challenges.
