Data Platform Purpose Catalogs for Scalable Compatibility Verification

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Data platforms face challenges in implementing data use controls that scale with increasing data volumes to comply with data protection regulations, particularly in ensuring that data is not misused for purposes not allowed by data subjects.

Innovation Solution

A metadata catalog is created to associate purposes with datasets, using an ontology of purposes to enable automated verification of compatibility and limitation of new processing activities, ensuring compliance with data protection regulations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual purpose verification is used, then data protection compliance can be ensured, but the system cannot scale with increasing data volumes

Engineering Contradiction:

Improvedata protection complianceVSAvoidscalability

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system enables self-service through automated purpose verification where the metadata catalog automatically verifies compatibility of processing purposes with stored data purposes, eliminating the need for manual verification while maintaining compliance

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical verification processes with an automated computational system that uses metadata catalogs and compatibility verification algorithms to automatically determine purpose compatibility at scale

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Object-affected harmful factors

If comprehensive purpose controls are implemented, then data misuse can be prevented, but implementation costs increase

Engineering Contradiction:

Improvedata misuse preventionVSAvoidimplementation cost

Core Design Contradiction:

Object-affected harmful factorsVSEase of manufacture

Solution Approach 1:

The metadata catalog serves multiple functions: it stores data purpose information, enables compatibility verification, supports consent management, and facilitates auditing, thereby preventing data misuse through a single unified system rather than multiple separate controls

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The metadata catalog acts as an intermediary layer between data processing activities and compliance requirements, enabling purpose verification without requiring direct complex controls at every processing point

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of manufacture

If existing metadata infrastructure is reused, then implementation costs are reduced, but purpose verification capability may be insufficient

Engineering Contradiction:

Improveimplementation costVSAvoidpurpose verification capability

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The patent merges existing metadata infrastructure with purpose verification functionality by integrating purpose information into the metadata catalog structure, allowing the same infrastructure to serve both traditional metadata storage and compliance verification functions

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20250252203A1Method, apparatus, and system for automated purpose limitation and compatibility verification on a data platform

Publication Date: 2025.08.07 HERE GLOBAL BV

AI summary

An approach is provided for automated purpose limitation and compatibility verification on a data platform. The approach, for example, involves generating metadata that indicates a purpose that has been allowed for processing a dataset. The approach also involves storing the metadata in a metadata catalog to associate the purpose with the dataset. The approach further involves querying the metadata catalog to perform a verification of a compatibility of the purpose with a requested purpose for a new processing activity of the dataset, to perform a limitation of the new processing activity, or a combination thereof.