Collaborative Real-Time Data Modeling via Knowledge Graphs
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Solution Overview
Problem
Users face challenges in making informed decisions due to the vast and unstructured nature of web data, which is time-consuming and labor-intensive to navigate, especially when seeking specific information or best practices from various sources.
Innovation Solution
The technology employs a hyper-local IoT data layer for real-time collaborative data modeling, combining cloud data, user knowledge graphs, telemetry data, and public data to provide personalized insights in 3-D or 2-D formats, enabling users to streamline decision-making processes by leveraging data from multiple sources, including user contributions and industry learnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users conduct web searches to find specific information for decision making, then they can access vast amounts of data from publicly available sources, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing data from multiple sources into structured knowledge graphs before users need it. Industry best practices, user contributions, and public data are aggregated and modeled in advance, so when a user has a decision to make, the relevant information is already prepared and can be quickly retrieved and presented, eliminating the need for time-consuming web searches.
Solution Approach 2:
The patent introduces an intermediary system that acts as a mediator between users and the vast web data. This intermediary (the data modeling system with knowledge graphs) processes, structures, and presents information in user-friendly formats, transforming raw web data into actionable insights. The intermediary handles the complexity of data collection and organization, allowing users to make decisions without directly navigating the overwhelming web data landscape.
2Reliability
If users start from scratch each time they need to make a decision, then they can ensure complete and thorough research, but the process becomes labor intensive and inefficient
Solution Approach 1:
The system merges multiple data sources including public data, industry best practices, user-generated content, and telemetry data into unified knowledge graphs. By combining these diverse sources and leveraging contributions from multiple users in the same line of business or with similar interests, the system provides comprehensive information that maintains research completeness while significantly improving efficiency through collaborative data sharing.
Solution Approach 2:
The system implements feedback mechanisms where user contributions and decisions are continuously incorporated into the knowledge graphs. As users make decisions and contribute data, this information feeds back into the system to improve future recommendations. This creates a self-improving system that maintains thoroughness while becoming increasingly efficient over time as the knowledge base grows and refines based on actual user behavior and outcomes.
3Device complexity
If the system presents data in traditional search result formats, then it maintains simplicity in data collection, but the information is not effectively presented to assist user decision making
Solution Approach 1:
The patent transforms data presentation from traditional two-dimensional search result text into three-dimensional visual models and immersive environments. The system renders knowledge graphs as 3D visualizations that users can explore interactively, adding spatial and contextual dimensions to data presentation. This dimensional transformation makes complex data relationships more intuitive and easier to understand, significantly improving decision-making ease while the system maintains relatively simple data collection processes behind the scenes.
Data Source
AI summary
Methods and systems are provided for facilitating collaborative real-time data modeling. Data corresponding to a particular subject from a plurality of sources is collected. The sources include a first data source having data corresponding to a first user and a second data source having data corresponding to a second user. For the first user, a first intent of the first user associated with content that is to be provided to the first user is determined. From the collected data, data associated with the determined first intent of the first user is identified. Output content for communication to a user device corresponding to the first user is generated in a format corresponding to the identified data.