VIS Query Mapping for Secure Cross-System Insight Aggregation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

The complexity of forming coherent and effective queries across multiple, disparate proprietary systems, coupled with the sensitive nature of data, impedes timely and accurate data insight aggregation, leading to inefficiencies and incomplete insights, particularly in healthcare.

Innovation Solution

An interoperable insight aggregation system using a query interpreter engine and a query mapper engine, aligned with a virtual information system, translates text-based insight requests into proprietary system queries, executing them locally to aggregate insights without exposing raw data, ensuring security and compliance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If queries are formed across multiple disparate proprietary systems, then comprehensive data insights can be obtained, but the complexity of query formation and system integration increases significantly

Engineering Contradiction:

Improvecomprehensive data insightsVSAvoidquery formation complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent introduces a natural language processing intermediary layer that translates user queries into system-specific queries. This mediator handles the complexity of interfacing with multiple disparate proprietary systems, allowing users to ask questions in natural language without needing to understand the underlying system complexities or data schemas.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments the complex task of cross-system querying into distinct components: natural language processing, query translation to various system formats, execution across multiple systems, and result aggregation. This segmentation allows each component to be optimized independently and simplifies the overall process for users.

Inventive Principle:

Principle #1Segmentation

2Loss of information

If data is shared across multiple entities, then aggregated insights can be achieved, but data security and privacy compliance become more challenging

Engineering Contradiction:

Improveaggregated insightsVSAvoiddata security risks

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

The patent extracts only the specific insights and answers needed from the distributed data sources rather than sharing the raw data itself. The system queries multiple entities, aggregates the results, and returns only the relevant insights to the user, leaving the sensitive underlying data securely contained within each entity's own system.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The centralized system acts as a secure intermediary that coordinates queries across multiple entities without exposing their data to each other. Each entity's data remains within its own secure boundaries, and the intermediary only handles aggregated results, thereby maintaining security while enabling insight sharing.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If proprietary interfaces are developed for data sharing, then data access can be enabled, but development and maintenance costs increase

Engineering Contradiction:

Improvedata access capabilityVSAvoiddevelopment cost

Core Design Contradiction:

Ease of operationVSEase of manufacture

Solution Approach 1:

The patent creates a universal natural language interface that works across multiple different proprietary systems without requiring custom integration for each system. This single multi-functional interface can query any connected data source using natural language, eliminating the need for separate proprietary interfaces for each system and significantly reducing development and maintenance costs.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If manual data collection methods are used, then specific health insights can be obtained, but time and resource consumption increase

Engineering Contradiction:

Improvehealth insight accuracyVSAvoiddata collection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical processes of data collection and analysis with an automated natural language processing system. The system automatically formulates, executes, and aggregates queries across multiple data sources, delivering precise health insights without the time-consuming manual efforts previously required for data collection and analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260045369A1System and method for aggregating insights from datasets dispersed across multiple disparate proprietary information systems

Publication Date: 2026.02.12 SVAFY LLC

AI summary

A system and method for aggregating insights from disparate proprietary information systems is disclosed. The system includes an insight aggregation server configured to receive a resource data mapper from each target entity of a plurality of target entities, each target entity having a target entity database. The resource data mapper maps its respective database to a virtual information system (VIS). The server is also configured to receive an insight request from a requesting entity in natural-language text form and transform it into a VIS-aligned query using a query interpreter engine, then transform the VIS-aligned query into target entity queries using a query mapper engine and the resource data mappers. Each target entity query is sent to the target entity it is aligned with, verified for authorization, and executed by that target entity database. The execution results from all target entities are then aggregated and provided to the requesting entity.