Geospatial Data Reconciliation via Alternative Geo-Descriptor Tables
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Solution Overview
Problem
Geospatial systems face challenges in displaying data accurately when location information is misspelled or represented differently, and require methods to import and reconcile large data sets without modifying the original data, especially with cost constraints.
Innovation Solution
A data reconciliation method that compares location fields against alternative geo-descriptors, generates a table with unique location IDs and metadata, and performs similarity searches to link location fields to geospatial shapes, allowing data to be displayed geographically without altering the original data set.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is imported into the geospatial system, then the system can display data geographically, but location mismatches prevent accurate display
Solution Approach 1:
The system performs preliminary actions by creating a comprehensive alternative geo-descriptor table before data import, containing multiple possible representations of each location (standard names, abbreviations, common misspellings). During data import, the system compares incoming location fields against this pre-prepared table to identify matches, resolving location mismatches automatically without requiring manual intervention during the import process itself.
Solution Approach 2:
The patent introduces an intermediary mechanism - the alternative geo-descriptor table with areaIDs - that acts as a mediator between the imported customer data and the geospatial system's internal location representations. This intermediary table contains multiple alternative descriptors for each standard location, enabling the system to bridge the gap between various data formats and the geospatial system's required format through automated comparison and matching.
2Reliability
If the system modifies original data to fix location errors, then geospatial display accuracy improves, but data integrity and customer requirements are violated
Solution Approach 1:
The system creates a copy of the location mapping information in the alternative geo-descriptor table, storing multiple representations of each location alongside the standard name and areaID. During data import, the system uses this copied reference information to identify matches and resolve location mismatches through metadata association rather than modifying the original customer data, thus preserving data integrity while achieving accurate geospatial display.
Solution Approach 2:
The alternative geo-descriptor table serves as an intermediary layer that preserves original customer data while enabling accurate geospatial display. The table contains areaID associations that link imported location fields to geospatial shapes without requiring modification of the source data, allowing the system to maintain both data integrity and geospatial accuracy simultaneously.
3Measurement precision
If manual verification is performed on all location fields, then location accuracy improves, but processing time and costs increase significantly
Solution Approach 1:
The system performs preliminary action by pre-populating the alternative geo-descriptor table with comprehensive location variations before the import process begins. During data import, the system automatically compares incoming location fields against this pre-prepared reference table using efficient string comparison algorithms, eliminating the need for manual verification of each location field while maintaining high matching accuracy.
Solution Approach 2:
The system enables self-service by implementing automated comparison logic that allows imported data to self-verify against the alternative geo-descriptor table. The system automatically identifies matches between incoming location fields and stored alternatives, resolving location mismatches without requiring manual intervention, thus significantly reducing processing time while maintaining accuracy.
Data Source
AI summary
In one embodiment, the present disclosure pertains to data import and reconciliation. In one embodiment, a location field is compared against alternative geo-descriptors to link the location fields to areaIDs and geospatial shapes. A similarity search is performed against unmatched location fields. In one example embodiment, a table is generated with unique location IDs, areaIDs, and metadata describing the results of the comparison.