Data quality in catalysis is important for several reasons:
Accuracy: Ensures that the experimental results are correct and reliable. Reproducibility: Enables other researchers to replicate the experiments and validate the findings. Optimization: Facilitates the fine-tuning of catalytic processes for better performance. Decision Making: Aids in making informed decisions regarding the development and application of catalysts.