What are the Key Features of a Data Lake for Catalysis?
1. Scalability: A data lake must be able to handle large volumes of data, which is essential for storing high-throughput screening results and large-scale computational simulations. 2. Flexibility: The ability to store different data formats (e.g., text, images, and numerical data) is crucial for capturing the breadth of information generated in catalytic studies. 3. Accessibility: Easy access to data for various stakeholders, including researchers, engineers, and data scientists, is necessary for collaborative work. 4. Security: Ensuring that sensitive data, such as proprietary research findings, is protected against unauthorized access.
