Which aspects contribute to the calculation of the validity of a dataset?

Comprehensive and Detailed Explanation:

The validity of a dataset in Talend's Trust Score™ framework is determined by:​

Number of valid and invalid values across the dataset sample (Option B):

This metric assesses the quality of the data by evaluating the proportion of valid entries compared to invalid ones. A higher number of valid values indicates better data quality.​

Use of semantic types across the dataset sample (Option C):

Semantic types help in understanding the meaning and context of data fields. Consistent and correct application of semantic types ensures that data is interpreted accurately, contributing to its validity.​

Why not other options?

Option A: User ratings and certification pertain to the popularity axis, reflecting user trust and endorsement, not the intrinsic validity of the data.​

Option D: The number of empty rows relates to the completeness axis, indicating missing data, rather than directly affecting validity.​