Metadata-Driven Operating Data Retention for Mobile Devices

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Solution Overview

Problem

Existing data management systems face challenges in efficiently managing large volumes of operating data from multiple devices, particularly in scenarios where different retention periods are required based on data content, leading to high storage and processing costs.

Innovation Solution

A method involving metadata analysis and a verification process using a knowledge-based processing system with a logic tensor network to detect and remove subsets of data based on meta-properties and time-dependent rejection criteria, ensuring efficient data reduction while maintaining relevant information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If large amounts of operating data from multiple devices are stored in a cloud data store, then data availability and processing capability are improved, but storage costs and data management complexity increase

Engineering Contradiction:
Improvedata availabilityVSAvoiddata volume
Core Design Contradiction:
ReliabilityVSQuantity of substance

Solution Approach 1:

The patent segments data into different categories based on metadata properties (e.g., operational data, diagnostic data, safety-critical data). Each segment has different retention policies and storage requirements, allowing the system to maintain data availability for critical segments while reducing storage volume for less critical segments.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies different quality standards and retention periods to different data segments. Critical data maintains high quality and long retention, while less critical data can be archived or deleted sooner, optimizing the balance between data availability and storage costs.

Inventive Principle:
Principle #3Local quality

2Reliability

If all operating data is retained indefinitely, then data completeness and legal compliance are improved, but storage costs and processing requirements increase

Engineering Contradiction:
Improvedata completenessVSAvoidprocessing energy
Core Design Contradiction:
ReliabilityVSLoss of energy

Solution Approach 1:

The patent implements dynamic retention policies that automatically adjust based on data properties, usage patterns, and legal requirements. The system dynamically evaluates data segments and applies different retention periods, deleting or archiving data that is no longer needed while maintaining completeness for critical data.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent changes retention parameters (storage period, access level, processing frequency) based on data metadata and business rules. This allows the system to maintain data completeness for essential data while reducing processing energy by excluding obsolete data from active processing.

Inventive Principle:
Principle #35Parameter changes

3Quantity of substance

If data is selectively removed based on retention criteria, then storage costs are reduced, but data availability and accessibility worsen

Engineering Contradiction:
Improvestorage volumeVSAvoiddata accessibility
Core Design Contradiction:
Quantity of substanceVSReliability

Solution Approach 1:

The patent performs preliminary classification of data into segments based on metadata before applying retention criteria. This preliminary action ensures that critical data is identified and protected from removal, while non-critical data can be safely deleted, maintaining accessibility where needed.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary data management layer that mediates between storage constraints and accessibility requirements. This layer classifies, prioritizes, and manages data segments, allowing the system to reduce storage volume while maintaining accessibility for critical data through targeted retention policies.

Inventive Principle:
Principle #24Intermediary (Mediator)

4Manufacturing precision

If a verification process is implemented to detect rejectability of data, then data quality and compliance are improved, but processing time and system complexity increase

Engineering Contradiction:
Improvedata qualityVSAvoidprocessing time
Core Design Contradiction:
Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent applies partial verification to data segments based on their criticality and retention requirements. Not all data undergoes full verification processes; instead, the system applies appropriate verification levels to each segment, reducing overall processing time while maintaining data quality where it matters most.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP4614339A1Method for data management of operating data in a data store, computer program product and system
Publication Date: 2025.09.10 VOLKSWAGEN AG
  • EP4614339A1 patent drawingFigure 1
  • EP4614339A1 patent drawingFigure 2
  • EP4614339A1 patent drawing

AI summary

The invention relates to a method (100) for data management of operating data (200) of a plurality of mobile devices (1), comprising: obtaining (102) the operating data (200) of the devices (1) with metadata (201) relating to the operating data (200), detecting (103) at least one meta-property (201.1) of the operating data (200) based on the metadata (201), and detecting (104) at least one time-dependent rejection criterion (202) for assignment to the meta-property (201.1). Furthermore, the invention relates to a computer program product and a system (3).