Proper data structuring is crucial for several reasons:
Data Integrity: Ensures that the data is accurate and consistent over its lifecycle. Interoperability: Facilitates data sharing between different research groups and software tools. Efficiency: Speeds up data retrieval and analysis processes. Reproducibility: Essential for validating experiments and simulations.
