Our final use case involves the evaluation of a new hypothesis based on existing data. Trotochaud and coworkers demonstrated that the activity of electrocatalysts for the oxygen evolution reaction (OER) may be enhanced due to incorporation of trace Fe impurities in standard electrolytes. Meanwhile, high throughput experiments revealed the broad range of compositions that are active OER catalysts in alkaline electrolytes. From these reports we can hypothesize that catalyst conditioning, perhaps through Fe incorporation, improves the activity of OER catalysts regardless of initial catalyst composition. This would imply that even poor catalysts will become competent catalysts upon aging, which has not been evaluated in the literature. Querying the MEKG for experiments of the type reported in Ref. produces a dataset of catalyst activity, where we group measurements by the primary element of the catalyst (concentration at least 70%) and consider the total duration of prior electrochemistry. Figure summarizes the results, revealing that all catalysts experience conditioning over 10's of seconds of electrochemical operation, and while transition-metal-rich catalysts exhibit the highest activity, the conditioning results in high activity for rare-earth-rich catalysts that otherwise may not exhibit such activity. A similar analysis in Figure shows that the same conditioning trend is observed in an alternate measurement of catalytic activity (catalyst overpotential at 3 mA/cm 2 ) in pH 13 electrolyte, while an opposite trend is observed in pH 7 electrolyte, indicating that catalyst instabilities outweigh any catalyst conditioning at near-neutral pH and demonstrating that evalaution of the aforementioned hypothesis pH-dependent. While the underlying high throughput experiments were not designed based on a catalyst conditioning hypothesis, the management of catalyst activity data in the context of experiment provenance enables rapid evaluation of such hypotheses using the MEKG.