Reusable Data Privacy Pipelines for Secure Data Collaboration
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Solution Overview
Problem
Existing data sharing techniques face challenges in facilitating collaborative intelligence while ensuring data privacy and controlling access, often preventing industries like healthcare and banking from sharing data due to concerns over confidentiality and competitive advantages.
Innovation Solution
A data collaboration tool that bundles data pipelines and contracts into a reusable template app, allowing developers to create placeholder elements, enabling collaboration without exposing underlying data, and provides debug modes using sample data or virtual assets for secure debugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is shared to bridge gaps in datasets and generate collaborative intelligence, then the value and completeness of data analysis is improved, but data privacy and confidentiality are compromised
Solution Approach 1:
The patent introduces a data trustee environment as an intermediary between data owners and data users. This mediator enables collaborative intelligence generation by processing and analyzing data without exposing the underlying sensitive information. The trustee environment acts as a secure buffer that allows data sharing while maintaining privacy through controlled access and processing mechanisms.
Solution Approach 2:
The patent creates template data privacy pipelines that can be copied and reused multiple times. These templates encapsulate the logic and structure for secure data processing, allowing the same privacy-preserving approach to be applied across different collaborations without recreating the security framework each time. The templates serve as reusable blueprints for secure data sharing arrangements.
2Ease of operation
If traditional data sharing methods are used to enable collaboration, then data accessibility is improved, but control over data access and usage is lost
Solution Approach 1:
The patent establishes data privacy pipelines and governing contracts in advance, before actual data sharing occurs. These pre-configured structures define the rules, permissions, and processing logic upfront, eliminating the need for complex access control negotiations during data collaboration. The preliminary setup enables seamless data access while maintaining control through pre-agreed terms.
Solution Approach 2:
The patent creates multi-purpose data privacy pipelines that can handle various data sharing scenarios through a single unified framework. The same pipeline structure can accommodate different data types, collaboration models, and privacy requirements, reducing the complexity of setting up access control for each specific case. This universal approach simplifies both accessibility and control management.
3Ease of manufacture
If reusable template pipelines are created to facilitate data collaboration, then the ease of deployment is improved, but the complexity of pipeline construction increases
Solution Approach 1:
The patent pre-configures data privacy pipelines with all necessary components, including processing logic, privacy controls, and governance rules, before deployment. This preliminary construction allows the pipelines to be reused as templates across multiple collaborations without requiring reconstruction. The upfront investment in pipeline design simplifies subsequent deployments while managing construction complexity through standardization.
Solution Approach 2:
The patent enables copying of established pipeline templates to create new data collaboration instances. Instead of building pipelines from scratch for each collaboration, the same proven templates can be replicated and adapted, reducing deployment effort. The copying mechanism preserves the complex internal structure while simplifying the deployment process for users.
4Ease of operation
If debug modes use sample data instead of production data, then debugging capability is improved, but measurement precision of data privacy pipeline performance deteriorates
Solution Approach 1:
The patent implements a dual-mode system where debug mode uses sample data for partial testing of pipeline logic and privacy controls, while production mode uses actual data for full performance validation. The debug mode provides sufficient testing capability for development purposes without requiring complete production data, accepting reduced measurement precision in exchange for enhanced debugging ease. This partial action approach allows iterative development with appropriate verification at each stage.
Data Source
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AI summary
Implementations are directed to developing and facilitating a data collaboration using a data collaboration tool that bundles data pipelines and governing contracts into a data collaboration app. The data collaboration tool may include an authoring mode and may include an electronic canvas that visually represents all contracts and pipelines of the data collaboration app on a single canvas and visually represents traceability from the contracts to the pipeline elements they enable. A developer may use authoring mode to develop a template app that includes placeholder elements, including a reference to an anonymous placeholder participant. The template app may be shared, and a recipient may invite data collaborators to fill in the placeholder elements and deploy the app, enabling the data collaborators to trigger the data pipelines to execute in a data trustee environment to generate insights from each other's assets without exposing the assets to the collaborators or the developer.