Historically, catalysts have been identified and their application optimised via empirical investigations, using previous success to guide future decision-making. Such "top-down" experimentation has recently seen the integration of high-throughput experimentation (HTE) into workflows, accelerating catalyst discovery through parallelisation of testing; in the more advanced cases, the HTE is coupled with datadriven analysis of reactivity/selectivity and automation to self-consistently optimise the efficacy of the catalytic system towards a target property, working within a defined parameter space. The current HTE approaches do not typically include advanced in situ or operando characterisation, but these methods are increasingly available separately and benefit from similar emergent capabilities in automated datadriven analysis.