Compliance with laws, regulations, or standards (Composition of datasets)
The degree to which the composition of datasets is in accordance with laws, regulations, or standards.
- •Ensures aggregated or derived datasets meet reporting standards and legal requirements.
- •Mitigates risks associated with inappropriate data aggregation or linkage (e.g., re-identification).
- •Supports ethical data use and responsible AI by adhering to composition rules.
- •Facilitates compliant data sharing and collaboration.
- •Violation of privacy laws or ethical guidelines through improper data aggregation or de-anonymization.
- •Non-compliant reporting if dataset composition does not meet specific standards (e.g., financial reporting rules).
- •Legal and reputational risks from misuse of combined datasets.
- •Barriers to data sharing if composition standards are not met.
Story
Logistics: Aggregated financial reports derived from multiple subsidiary datasets comply with IFRS or GAAP reporting standards.
Marketing: Customer segments created for targeted advertising are based on aggregated, anonymized data that respects privacy regulations and user consent.
Research: When combining datasets for a study, all data linkage and aggregation methods follow strict protocols to maintain anonymity and comply with IRB approvals.
Logistics: Combining employee performance data with anonymous survey data in a way that inadvertently allows re-identification of individuals, violating privacy policies.
Marketing: Creating customer profiles by combining data from various sources without explicit consent for such aggregation, potentially violating data privacy laws.
Research: A dataset compiled for public release aggregates sensitive demographic data in such a way that small population groups could be identified, breaching ethical guidelines.