The complexity and vast amount of data generated in catalytic research necessitate robust mechanisms for data management. Automated labeling systems reduce human error, save time, and increase the accuracy of data categorization. This, in turn, facilitates better data analysis, accelerates discovery processes, and aids in the development of more efficient and effective catalysts.