Automatic transparency evaluation for open knowledge extraction systems

Table 2 Differences and commonalities between data transparency methods

Data transparency methods	Transparency information
Data transparency methods	Data retention information	Fairness indicators	Collection mechanism	Validation and verification	Errors, noise, redundancies	Missing values	Maintenance	Preprocessing, cleaning, labelling	Dataset statistics
Datasheets [45]	\(\checkmark\)	×	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	×
Data Cards [46]	×	\(\checkmark\)	\(\checkmark\)	×	×	×	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)
Data Nutrition Labels [47]	×	×	×	×	×	\(\checkmark\)	×	×	\(\checkmark\)

ISSN: 2041-1480