Staged Resource Querying for Dynamic Graph-Based Organization
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Solution Overview
Problem
Traditional file systems and content management solutions struggle with inflexible hierarchical structures, limited resource type support, inefficient querying mechanisms, and inability to handle complex transformations and derived resources, particularly in modern computing environments with diverse digital assets.
Innovation Solution
A staged query system that processes digital resources through a sequence of customizable stage types, allowing for dynamic graph organization, incremental processing, and flexible querying across multiple providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional hierarchical folder structures are used to organize resources, then resources can be grouped in a simple structure, but the system becomes inflexible and cannot handle diverse digital asset types effectively
Solution Approach 1:
The patent segments the resource organization into two independent parts: a unified hierarchical structure for organization and a virtual tag graph for diverse categorization. Resources are segmented from their traditional folder locations and reassigned to virtual containers based on multiple tag dimensions, allowing one resource to belong to multiple hierarchical levels and tag categories simultaneously without structural conflicts.
Solution Approach 2:
The patent introduces a virtual tag graph as an intermediary layer between resources and the hierarchical structure. This virtual tag graph acts as a mediator that maps diverse resource types to the unified hierarchy through tag-based associations, enabling flexible organization without modifying the underlying hierarchical structure or requiring resources to be physically relocated.
2Adaptability or versatility
If resources are tightly coupled with their organizational structure, then the structure is simple to implement, but multiple organizational views cannot be created without duplicating data
Solution Approach 1:
The patent creates virtual copies of resources through tag-based associations rather than physical duplications. Each resource maintains a single physical location but can be virtually copied to multiple organizational views through tag graph connections, allowing the same resource to appear in different hierarchical contexts without creating duplicate data storage.
Solution Approach 2:
The patent makes the tag graph universal by allowing it to serve multiple organizational purposes simultaneously. The same tag graph structure can support different organizational views, search queries, and resource groupings without requiring separate data structures, enabling one system to fulfill multiple organizational functions.
3Difficulty of detecting and measuring
If conventional query mechanisms are used, then resource discoverability is basic, but advanced querying and filtering mechanisms are lacking for large-scale datasets
Solution Approach 1:
The patent performs preliminary organization of resources into the virtual tag graph structure during data ingestion, so that complex queries can be answered by traversing pre-established tag relationships rather than performing complex filtering operations on raw data. This preliminary structuring enables efficient querying without requiring complex query processing mechanisms at runtime.
4Adaptability or versatility
If flat single-level grouping is used for resources, then the structure is simple to implement, but complex hierarchical organizational structures cannot be created
Solution Approach 1:
The patent implements nesting by allowing virtual containers to be contained within other virtual containers through the tag graph hierarchy. A resource can be nested at multiple levels by assigning it to multiple parent containers through different tag paths, creating a nested hierarchical structure where containers can be organized in multiple dimensions simultaneously without structural conflicts.
Data Source
AI summary
A computer-implemented system and method for staged resource querying addresses limitations of traditional file systems, which provide a flexible, scalable framework for organizing, managing, and querying diverse digital resources across multiple providers. The method receives a query specifying a sequence of stage types, each defining processing and grouping of items. It executes operations to process input items through these stages, creating a dynamic graph structure of grouped output items. This includes taking items from a resource iterator, processing them through specified stages, and organizing results into groups. The method enables incremental processing of resources, allowing efficient handling of large datasets and complex queries. It provides mechanisms for propagating items through the stage graph, offering fine-grained control over resource processing and grouping at each stage. This approach enables powerful, flexible querying and organization of digital resources, addressing limitations of traditional file systems and content management solutions.