Unified Data Structure for Cross-Application Record Keeping
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Solution Overview
Problem
Individuals face challenges in maintaining accurate and complete records due to fragmented data across multiple applications and sources, making it difficult to access and cross-reference information for record-keeping tasks like financial accounting and income-tax preparation.
Innovation Solution
A system that aggregates information from multiple sources based on user preferences, identifies ambiguities, and prompts users for clarification, using techniques like web scraping and meta-data classification to collect and classify record-keeping information from financial, email, calendar, and document-management software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple applications with fragmented data structures, then information can be managed across different applications, but it becomes difficult to access and cross-reference information
Solution Approach 1:
The patent combines fragmented data from multiple applications into a unified data structure that consolidates information from calendar, email, contacts, and other sources. This unified structure enables cross-referencing and comprehensive access to information without requiring users to navigate multiple separate applications, thereby improving information accessibility while managing complexity through centralized organization.
Solution Approach 2:
The patent introduces an intermediary component that acts as a bridge between multiple applications with different data structures and the user. This intermediary layer translates and integrates data from various sources into a common format, allowing users to access information from multiple applications through a single interface without directly dealing with the complexity of each application's native data structure.
2Reliability
If users manually maintain records across multiple applications, then record-keeping can be performed, but the process becomes increasingly difficult and time-consuming
Solution Approach 1:
The patent implements self-service functionality where the system automatically aggregates, consolidates, and organizes data from multiple applications without requiring manual user intervention. The unified data structure automatically updates as new information is added to source applications, and the system independently maintains record completeness by continuously syncing with source applications, thereby eliminating the time users would otherwise spend manually maintaining records.
Solution Approach 2:
The patent performs preliminary actions by pre-aggregating and organizing data from multiple applications into the unified data structure in advance. This preliminary consolidation ensures that when users need information for record-keeping, it is already organized and ready for use, eliminating the need for time-consuming manual gathering and organization of data at the moment of need.
3Adaptability or versatility
If applications are not configured to communicate with each other, then each application can function independently, but users cannot collect information for cross-application referencing and chronological record-keeping
Solution Approach 1:
The patent creates a universal data structure that can accommodate and integrate information from multiple different application types (calendar, email, contacts, etc.) through a single unified format. This universal structure enables cross-application referencing and chronological record-keeping by providing a common framework that can represent data from diverse sources in a consistent manner, thereby achieving adaptability without requiring complex custom integration for each application pair.
Data Source
AI summary
A system for collecting information is described. During operation, this system aggregates information from multiple information sources based on user preferences. Then, the system requests additional information from a user about ambiguities or variations in the aggregated information. These ambiguities are associated with changes in user activities, and the changes may be determined using a user-activity history and/or user preferences. Note that the system can repeat the aggregating and requesting operations multiple times.