Data curation in catalysis involves multiple steps:
Collection: Data is collected from experiments, publications, and digital sources. Cleaning: Removing any errors or inconsistencies in the data to ensure accuracy. Annotation: Adding metadata and notes to provide context and make the data more useful. Storage: Storing data in structured formats such as databases or repositories. Sharing: Making data accessible to other researchers through open-access platforms or collaborations.
