Geocoded Data Management via Entity-Attribute-Value Database
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Solution Overview
Problem
Traditional relational databases face inefficiencies when managing and retrieving geographically coded data due to their design constraints, leading to slow performance and inefficiencies in querying large datasets with many demographic and statistical fields, especially when data is only defined for certain geographic subdivisions.
Innovation Solution
The system employs an entity-attribute-value (EAV) database to store geographically coded data, using geographic overlap to map data from one subdivision to another, allowing for efficient retrieval and transformation of data across different geographic boundaries, thereby enhancing query performance and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional relational databases are used to store geographically coded data, then data structure simplicity is maintained, but query performance deteriorates when dealing with large datasets and multiple geographic subdivisions
Solution Approach 1:
The patent segments the database into multiple geographic subdivision tables (e.g., census tract table, neighborhood table, community area table) that can be independently queried and joined. This segmentation allows the system to handle large datasets by dividing them into manageable geographic units, improving query performance when dealing with specific geographic subdivisions while maintaining a structured approach to data organization.
2Loss of information
If data is stored for multiple geographic subdivisions in traditional relational databases, then data completeness is improved, but retrieval efficiency deteriorates due to design constraints
Solution Approach 1:
The patent implements preliminary action by pre-computing and storing geographic hierarchy relationships and overlap information in the database schema. The geographic subdivision tables are pre-configured with spatial relationships, allowing the system to quickly retrieve data across multiple geographic levels without performing complex calculations at query time, thus reducing retrieval time while maintaining data completeness.
3Adaptability or versatility
If traditional relational databases manage geographically coded data, then ease of operation is maintained, but scalability deteriorates when handling diverse geographic data sets
Solution Approach 1:
The patent creates a universal geographic subdivision framework where a single database schema can handle multiple types of geographic subdivisions (census tracts, neighborhoods, community areas) through standardized table structures. This universal approach allows the system to scale to diverse geographic datasets while maintaining ease of operation through consistent query patterns and a unified interface for accessing geographic data across different levels.
Data Source
AI summary
Method and apparatus are disclosed for a system and method for managing and retrieving disparate geographically coded data in a database. An example system for processing a search query for geocoded data includes a database with the geocoded data associated with first and second geographic subdivisions and a computing device. When new geocoded data associated with the first geographic subdivision is not associated with the second geographic subdivision, the computing device generates values associated with the second geographic subdivision for the new geocoded data based on geographic overlap of the first and second geographic subdivisions and inserts the values into the entity-attribute-value database. In response to receiving a query from one of the end-user devices for the new geocoded data associated with the second geographic subdivisions, the computing device provides the values in a query response.