Data sharing is crucial in catalysis for several reasons:
Accelerating Research: By sharing data, researchers can build upon each other's work, avoiding duplication of efforts and speeding up the discovery of new catalysts. Improving Reproducibility: Shared data allows other researchers to reproduce experiments, which is essential for validating results and conclusions. Enhancing Collaboration: Data sharing fosters collaboration between different research groups and industries, leading to more comprehensive and innovative solutions. Enabling Machine Learning: Large datasets are necessary for training machine learning models, which can predict catalyst performance and guide experimental efforts.
