What challenges are associated with data complexity in catalysis?
One of the main challenges is the high dimensionality of the data, which makes it difficult to visualize and interpret. Additionally, the data can be noisy and incomplete, requiring robust preprocessing and cleaning techniques. The non-linear interactions between variables add another layer of complexity, making it hard to develop accurate predictive models. Furthermore, integrating data from different sources, such as experimental and computational data, can be challenging due to differences in scale and formats.
