Tag Management System for Automated Data Resolution
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Solution Overview
Problem
The process of identifying related data items in documents and establishing associations with external data sources is cumbersome and prone to errors, requiring manual searches across multiple databases, which is inefficient and time-consuming.
Innovation Solution
A data resolution system that allows users to create associations between data items tagged in documents, automatically identifying related data items from external sources during the tagging process, storing this information for easy access, and providing interactive and dynamic user interfaces for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual searching across multiple external databases is performed to identify related data items, then associations between tagged items and external data sources can be established, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically searching external data sources and identifying related data items during the initial tagging process, before the user needs to access the information. This pre-computation eliminates the need for manual searching later, resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The system serves itself by automatically performing data resolution and association tasks without requiring manual intervention. The automated search and matching mechanisms handle the identification of related data items independently, improving both speed and consistency while reducing human effort.
2Ease of operation
If users manually search and identify related data items in external databases, then associations can be created, but the process is prone to errors
Solution Approach 1:
The system replaces the manual mechanical process of searching and matching data with an automated computational system. The computer automatically queries external data sources, compares data items, and establishes associations, eliminating human error while maintaining ease of operation through automated workflows.
Solution Approach 2:
The system incorporates feedback mechanisms where the automated search results are validated and refined based on matching criteria, ensuring high accuracy in identifying related data items. The feedback loop allows the system to adjust and improve association accuracy while maintaining operational simplicity.
3Productivity
If multiple users access documents and individually search for related data items, then each user can find information, but computer processing resources are wasted
Solution Approach 1:
The system merges the data resolution functionality into the document ingestion process itself. By combining the search and association tasks into a single automated workflow during ingestion, the system eliminates redundant processing when multiple users access the same documents, reducing energy consumption while maintaining high productivity.
Solution Approach 2:
The automated data resolution system provides universal service to all users simultaneously. Once data associations are established during ingestion, all users benefit from the pre-computed relationships without needing to perform individual searches, making the system multi-functional and energy-efficient.
4Ease of operation
If comprehensive data from external sources is made accessible during tagging, then users can identify related items more easily, but the system complexity increases
Solution Approach 1:
The system extracts only the necessary data elements from external sources that are relevant to the tagging process. By selectively retrieving and displaying only the essential information needed for identification, the system maintains ease of operation while avoiding the complexity of managing and presenting comprehensive data sets.
Data Source
AI summary
A data resolution system provides users with the ability to access and create associations between data items tagged in documents as part of an initial process of identifying data items to be tagged in the documents. Thus, the user that is adding tags to the documents is able to identify related data items from other data sources and create links with those data sources. This ability to identify links at the time of tagging reduces the need for later searching of data sources for related data items. Additionally, the system automatically stores information regarding each link so that information regarding the linked data items may be viewed alongside the original document and/or further information regarding the linked data item is easily accessible. Data items that are tagged in a document may be associated with data items representing the same object, but with different identifiers, names, etc. in external data sources.