Dynamic File Graph for Metadata Lifecycle Tracking
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Solution Overview
Problem
Current file system technologies fail to effectively track and manage the lifecycle of documents and files across an organization, leading to security issues, data loss, and inefficient content management due to incomplete metadata tracking and lack of multidimensional search capabilities.
Innovation Solution
A graph data structure is dynamically built to represent file lifecycles by analyzing metadata transitions, allowing for the inference of state changes and visualization of content dissemination, enabling organizations to identify content creators, replicators, and communication patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional file system metadata tracking is used, then file storage and basic management are maintained, but comprehensive lifecycle tracking and multidimensional search capabilities are insufficient
Solution Approach 1:
The patent introduces a graph database as an intermediary layer between the traditional file system and the metadata tracking requirements. The graph database receives file metadata from the file system and stores it in a structured format that enables comprehensive tracking and multidimensional search, without modifying the underlying file system structure.
Solution Approach 2:
The patent adds a new dimension to file metadata storage by implementing a graph-based data structure that captures relationships between files, users, devices, and actions. This graph dimension enables multidimensional search capabilities and comprehensive lifecycle tracking while the original file system structure remains intact.
2Productivity
If comprehensive metadata tracking is implemented, then file lifecycle management is improved, but search capability and analysis depth are enhanced
Solution Approach 1:
The graph database structure enables feedback mechanisms where file relationships and metadata are continuously tracked and made queryable. This allows the system to provide comprehensive information about file lifecycles, user interactions, and content relationships, improving content management efficiency through informed decision-making.
Solution Approach 2:
The graph database serves multiple functions simultaneously: it stores file metadata, tracks file relationships, enables multidimensional search, and supports security policy enforcement. This multi-functionality improves productivity by consolidating various content management tasks into a single system.
3Reliability
If graph database is used for multidimensional search, then security measures and content management policies can be applied, but system complexity increases
Solution Approach 1:
The patent segments the system into two distinct parts: the traditional file system for storage and the graph database for metadata tracking and analysis. This segmentation allows each component to specialize in its function, with the graph database handling security and policy enforcement without complicating the file system structure.
Solution Approach 2:
The graph database acts as an intermediary that enforces security measures and content management policies based on the tracked metadata and relationships. It provides the analytical layer needed for security decisions without requiring changes to the underlying file system, maintaining reliability while managing complexity.
Data Source
AI summary
System and techniques for dynamically building a file graph are described herein. Meta data is received for a first and a second file. An intersection of the first metadata set and the second metadata set is computed. An edge in a file graph is created based on the intersection. Then, after receiving a query about the first file, the second file is provided as a result to the query based on the edge in the file graph.