Effective data structuring involves several steps:
Metadata Annotation: Adding descriptive metadata to each dataset to provide context. This includes information like the date of creation, experimental parameters, and the names of researchers involved. Standardized Formats: Using standardized file formats (like CSV, JSON, or HDF5) to ensure compatibility and ease of use across platforms. Database Management Systems (DBMS): Utilizing relational databases (like SQL) or NoSQL databases (like MongoDB) for structured storage and fast retrieval. Data Ontologies: Implementing ontologies like the Nanoparticle Ontology (NPO) to standardize terminology and data relationships.
