Searchable Contextual Actions Across Fragmented Workflow Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional productivity systems require high processing power and storage costs due to data fragmentation across multiple repositories, and burden users with manual identification of related work components, leading to inefficiency and negative user experiences.
Innovation Solution
A workflow management system that automatically identifies and links related components of work across various systems, eliminating the need for central data repositories and manual tagging, using a server to generate unique identifiers and nodal data structures for real-time data presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored on a central electronic data repository, then data management is centralized, but processing power requirements and storage costs increase significantly
Solution Approach 1:
The patent segments data storage and management across multiple distributed repositories instead of using a single central repository. Each repository maintains local data, and the system uses distributed indexing and metadata management to enable centralized-like control without the processing burden of a single central system. This segmentation reduces the processing power requirements at any single point while maintaining data management reliability.
Solution Approach 2:
The patent introduces an intermediary layer (distributed file system or network file system) that sits between users and the actual data repositories. This intermediary handles metadata management, file indexing, and coordination tasks, allowing multiple distributed repositories to function together as a unified system without requiring each repository to handle the full processing load of a central system.
2Reliability
If data is stored on a central electronic data repository, then data management is centralized, but storage costs increase
Solution Approach 1:
The patent divides storage across multiple repositories, allowing organizations to use existing storage infrastructure from different providers rather than investing in a single large central storage system. This segmentation enables cost-effective utilization of distributed storage resources while maintaining data management reliability through the coordinated access mechanisms provided by the distributed file system.
3Loss of information
If users manually identify and tag related components of work, then relationships between files are documented, but user burden increases and user experience deteriorates
Solution Approach 1:
The patent implements automatic relationship detection and tagging mechanisms that analyze file contents, metadata, access patterns, and user interactions to identify and establish relationships between components of work automatically. This self-service approach eliminates the need for users to manually tag and categorize files, reducing user burden while maintaining accurate relationship documentation through automated analysis of contextual data.
4Loss of time
If conventional productivity systems monitor files in real-time, then timely access to file relationships is achieved, but processing power requirements increase
Solution Approach 1:
The patent implements periodic monitoring and relationship detection instead of continuous real-time monitoring. The system periodically scans files, updates metadata, and detects relationships at scheduled intervals, which significantly reduces processing power requirements compared to continuous monitoring while still providing timely access to file relationships for most practical purposes.
Solution Approach 2:
The patent performs preliminary indexing and metadata generation when files are created or modified, preparing relationship data in advance. This preliminary action reduces the need for intensive processing during monitoring operations, as the system can query pre-computed metadata and indexes rather than analyzing file contents in real-time, thereby reducing processing power requirements while maintaining timely access.
Data Source
AI summary
Disclosed methods and systems allow a central server to monitor electronic units of work accessible to a group of computers and generate a nodal data structure representing the units of work. The server then uses various protocols, such as hashing algorithms and/or executing artificial intelligence and machine learning models to identify similar and/or related units of work. The server then merges/links the nodes corresponding to the similar/related units of work. The server also monitors all user activities. When a user or a software system/service accesses electronic content on his, her, or its electronic device, the server identifies a node corresponding to the accessed electronic content and associated unit(s) of work and presents searchable data and actions related to the identified node and any related/linked nodes.