Webform Crawling Data Model for Privacy Compliance
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage personal data in compliance with privacy and security policies, as frequent breaches and unauthorized access to sensitive information have become more common, and individuals seek tools to minimize data processing by entities they do not actively engage with.
Innovation Solution
A computer-implemented data processing method that modifies a data model by identifying and analyzing webforms to collect personal data, determining processing activities, and associating data assets, allowing for the management and storage of personal data in a third-party repository with enhanced security and compliance measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If organizations collect and store personal data across multiple systems and webforms, then data availability for business operations is improved, but data security and compliance management become more difficult
Solution Approach 1:
The system segments data management by creating separate data inventories for different data assets while maintaining a unified data model that connects them. Each data asset (e.g., customer database, webform) has its own inventory tracking specific data elements, but all are integrated through the centralized data model that enforces compliance policies across the entire organization.
Solution Approach 2:
The patent introduces a centralized data model as an intermediary layer between individual data assets and compliance management systems. This data model serves as a mediator that standardizes data representation, tracks data flows, and enforces security policies without requiring changes to underlying data collection systems.
2Device complexity
If manual processes are used to track data processing activities, then implementation complexity is reduced, but time consumption and inefficiency increase
Solution Approach 1:
The system enables self-service data tracking by automatically discovering data assets, extracting data element information from webforms and databases, and populating the data model without requiring manual intervention. The automated discovery processes continuously monitor data flows and update inventories, eliminating the need for manual tracking while maintaining simplicity in deployment.
Solution Approach 2:
The patent implements preliminary action by pre-defining data element schemas and compliance rules in the data model before data collection occurs. This allows the system to automatically validate and track data processing activities against predetermined standards, eliminating the need for manual analysis and reporting while reducing implementation complexity.
3Ease of operation
If data is stored in multiple locations across different systems, then data accessibility is improved, but redundant storage and security risks increase
Solution Approach 1:
The centralized data model serves multiple functions simultaneously: it provides a unified view of all data assets for accessibility, tracks data flows to identify redundancy, enforces security policies, and manages compliance requirements. This multi-functional approach eliminates the need for separate systems for each function, reducing redundant storage while maintaining data accessibility.
4Reliability
If comprehensive data tracking is implemented across all systems, then compliance monitoring is improved, but system complexity and resource requirements increase
Solution Approach 1:
The system creates simplified copies of data asset information in the centralized data model, rather than duplicating entire data systems. The data inventory captures essential metadata and data element information from source systems, allowing compliance monitoring without requiring direct access to or complexity of the underlying data collection systems.
Data Source
AI summary
In particular embodiments, a Data Access Webform Crawling System is configured to: (1) identify a webform used to collect one or more pieces of personal data; (2) robotically complete the identified webform; (3) analyze the completed webform to determine one or more processing activities that utilize the one or more pieces of personal data collected by the webform; (4) identify a first data asset in the data model that is associated with the one or more processing activities; (5) modify a data inventory for the first data asset in the data model to include data associated with the webform; and (6) modify the data model to include the modified data inventory for the first data asset.