Mapping System Model Editor with Automated Data Validation
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Solution Overview
Problem
Computer-implemented mapping systems face challenges in efficiently managing and maintaining accurate graphical and non-graphical data associated with fixed objects, particularly in updating information related to businesses and locations, which is time-consuming and complex due to the vast and dynamic nature of this data.
Innovation Solution
A system and method that allows users to edit and confirm graphical and non-graphical data associated with models representing physical objects in a web-enabled mapping system, utilizing a model editor module to create, upload, and associate models with geographic locations, with a data review module to validate changes against predefined rules and timestamps, ensuring data accuracy and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are allowed to freely edit and upload graphic components and associated data, then the system's adaptability and user engagement improve, but data accuracy and consistency deteriorate
Solution Approach 1:
The system implements automated feedback loops where uploaded graphic components and associated data undergo validation against predefined rules. The validation process provides immediate feedback to users about data quality issues, requiring corrections before acceptance. This ensures continuous improvement of data accuracy while maintaining user editing capabilities.
Solution Approach 2:
An intermediary validation layer is introduced between user uploads and the master database. This intermediary process automatically checks graphic components and associated data against consistency rules, acting as a mediator that filters out inaccurate information while allowing legitimate user contributions to pass through.
2Reliability
If comprehensive validation rules are applied to all uploaded data, then data accuracy improves, but processing time and system complexity increase
Solution Approach 1:
The validation system is segmented into modular rule sets that can be independently configured and executed. Different validation rules are applied to different types of graphic components and data fields, allowing the system to manage complexity through division while maintaining comprehensive validation coverage.
Solution Approach 2:
The system dynamically adjusts validation parameters based on the type of graphic component being uploaded. Different parameter sets are applied depending on whether the upload is a building model, street feature, or point of interest, optimizing the validation process for each specific case rather than applying a single complex rule set to all data.
3Reliability
If manual review processes are used to verify uploaded data, then data accuracy improves, but processing speed and productivity decrease
Solution Approach 1:
The system implements self-service validation where the automated rule-based validation process performs the verification function that would otherwise require manual review. The system serves itself by automatically detecting and flagging inconsistent data, eliminating the need for human reviewers to perform routine verification tasks while maintaining high accuracy standards.
Solution Approach 2:
Manual mechanical review processes are replaced with an automated electronic validation system that uses predefined rules and algorithms to verify uploaded data. This substitution of mechanical human review with an electronic automated system dramatically increases processing speed while maintaining verification accuracy.
4Loss of information
If extensive data collection is performed to maintain comprehensive databases, then information completeness improves, but maintenance complexity and time requirements increase
Solution Approach 1:
Validation rules are established in advance before data uploads occur. These pre-configured rules automatically check for completeness and consistency issues during the upload process itself, rather than requiring separate maintenance operations later. This preliminary validation action prevents incomplete data from entering the database, reducing future maintenance needs.
Solution Approach 2:
The validation process operates continuously in the background during data uploads without requiring separate batch processing or manual intervention. The useful action of data verification is performed continuously as part of the normal upload workflow, eliminating idle time and maintaining constant data quality assurance.
Data Source
AI summary
A computer-implemented system, method, or computer-readable medium storing a set of instructions for execution on a processor may edit and confirm data associated with geographic locations shared by models graphically representing physical objects corresponding to geographic locations displayed in a web-enabled mapping system. This may allow a user to edit or create a graphic component corresponding to a model and receive an edited or created model at the mapping system. The user may also change or supplement graphical and non-graphical data corresponding to the model's location in response to receiving the edited or created model at the mapping system, and determine if the user changed or supplemented the non-graphical data associated with the model. This changed data may also be reviewed against rules to determine if it should be associated with the model that is displayed in the mapping system.