How does the framework define Small Data?

1. The definition reads: "Small Data refers to the limits in the size of datasets that analysts can fully evaluate and understand." 2. Read it carefully: the definition is about a human limit, not a hardware limit. The boundary is what a person can fully evaluate and understand, not what a machine can hold. 3. That is why the option about fitting in one machine's memory is wrong even though it sounds like the obvious meaning. The framework never draws the line at hardware capacity. 4. A representative subset drawn from a larger population is data sampling, which the framework discusses separately under data science. A sample is deliberately taken from a bigger set Small Data is simply data that is already within human reach. 5. Data with a predefined model or organisation is the definition of structured data, which is a statement about form rather than size. 6. The term matters because it sets up the framework's central claim by contrast: Big Data is the case where the scale of the data itself "causes the management of the data to be a significant driver in the design of the system architecture". _Source: NIST SP 1500-1r2 "NIST Big Data Interoperability Framework: Volume 1, Definitions" (Oct 2019), p.7 section 2 "Terms and Definitions"_