Multi-dimensional Representation Object for Context-Preserving Data Aggregation
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Solution Overview
Problem
Users face difficulties in efficiently accessing and presenting specific sections or data segments from multiple source documents, leading to time-consuming searches and potential errors when sharing or reviewing information.
Innovation Solution
The development of computer-implemented methods and systems for creating and consuming multi-dimensional representations (MDRs), which combine data segments from various sources into a unified format, including resource metadata for context preservation and controlled updates, allowing for easy insertion and consumption across different applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users manually search and access specific data segments from multiple source documents, then they can retrieve the needed information, but it is time-consuming and error-prone
Solution Approach 1:
The system performs preliminary actions by automatically identifying, extracting, and organizing data segments from multiple source documents before the user needs them. MDR objects are pre-created with embedded metadata including source document identifiers, resource types, and coordinate information, so when users need specific data segments, they are immediately available without manual searching or manual creation of references.
2Productivity
If users share documents by attaching entire files or sending links, then they can share information with other users, but it is inefficient and lacks precision
Solution Approach 1:
The system extracts only the specific data segments that are relevant to the sharing purpose, rather than sharing entire documents. MDR objects contain extracted data segment information with embedded metadata that identifies the source document, resource type, and precise location (coordinates), allowing users to share only the necessary portions of information while preserving full context about the original source.
Solution Approach 2:
The system adds a new dimension to document sharing by creating multi-dimensional representations that include not just the data segment content but also metadata dimensions such as source document identification, resource type, and coordinate information. This allows precise sharing of specific segments while maintaining links to original sources, enabling both efficiency and context preservation simultaneously.
3Reliability
If users manually track and manage data segments from multiple sources, then they can maintain data context, but it increases complexity and potential for errors
Solution Approach 1:
The system merges the data segment content with its metadata (source document identification, resource type, coordinates) into a single unified MDR object. This combination eliminates the need for separate tracking systems while maintaining complete context information. The MDR object structure integrates all necessary elements for data integrity in one cohesive unit that can be easily created, stored, and managed.
Data Source
AI summary
The disclosure generally describes methods, software, and systems, including a method for creating a multi-dimensional representation (MDR). A creation request is received to create an MDR referencing at least one identified data segment in each of at least a first source document. An MDR object is generated that includes data segment information for the at least one identified data segment and a set of resource metadata comprising, for each data segment, an identification of a source document that includes the particular identified data segment, a resource type of the source document, and a set of coordinates associated with the particular identified data segment within the source document. The MDR object is stored to a clipboard containing MDR objects. An insertion request is received to insert the stored MDR object into a target document. The stored MDR object is inserted from the clipboard into a target document.