Ontological Vector Map Tile Generation for Non-GIS Users
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Solution Overview
Problem
Current systems lack the ability to easily generate and provide custom ontological vector map tiles layers from geo-spatial datasets, making it difficult for users to interact with and analyze geo-spatial data, especially for non-GIS experts, and fail to incorporate external data effectively into map visualizations with a time dimension.
Innovation Solution
A software application that treats geo-spatial features as logical entities, allowing users to create and interact with custom vector layers on a map, generating vector map data layers from ontological datasets, incorporating external data, and enabling temporal data visualization by enriching map data tiles on-demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users define custom vector layers with large amounts of geo-spatial data, then the map can display comprehensive geographic information, but non-GIS experts find it difficult to properly place and scale the data
Solution Approach 1:
The system introduces an intermediary layer between the user and the complex geo-spatial data processing. The backend service acts as a mediator that automatically handles data transformation, coordinate reference system conversion, and vector tile generation. Users simply point to datasets through intuitive UI elements without needing to understand the underlying GIS complexity, thus resolving the contradiction between data comprehensiveness and ease of operation.
Solution Approach 2:
The system enables self-service by automatically processing geo-spatial data without requiring user expertise. The backend services autonomously perform data validation, coordinate transformation, and vector tile generation based on user selections. This automation allows non-GIS experts to work with large geo-spatial datasets effortlessly, maintaining both data quantity and operational ease.
2Adaptability or versatility
If external data is accessed to enrich map geometries, then more comprehensive analysis is enabled, but the data may not exist as vector map tiles and cannot be easily integrated
Solution Approach 1:
The system performs preliminary action by pre-processing external data into vector tile format before it is needed for mapping. The backend service proactively transforms external datasets into the required vector tile structure with appropriate coordinate references, so when users access external data, it is already ready for immediate integration into the map visualization, eliminating integration complexity.
Solution Approach 2:
The backend service functions as an intermediary that bridges external data sources and the map visualization system. It automatically converts external data formats into compatible vector tile structures, handles coordinate reference system transformations, and integrates the enriched data with existing map geometries. This intermediary layer simplifies the entire process for users while maintaining data versatility.
3Productivity
If map data tiles are enriched on-the-fly with external data, then dynamic and comprehensive data access is enabled, but system complexity increases
Solution Approach 1:
The system implements preliminary action by pre-generating and caching vector tiles with enriched data in the backend. When users access data, the system retrieves pre-processed tiles rather than processing data in real-time, significantly improving access speed. The complex processing is performed beforehand during data ingestion or scheduled tasks, keeping the user-facing system simple and fast.
Solution Approach 2:
The system segments the data processing into distinct phases: data ingestion, transformation, enrichment, and serving. The backend service handles complex processing during ingestion and caching phases, while the frontend system simply serves and displays pre-processed vector tiles. This segmentation isolates complexity to the backend while maintaining simple, fast user interaction through the map interface.
Data Source
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AI summary
Systems and methods for preparing and analyzing data related to geo-spatial properties. A system generates from a first data source, based on an ontology, a geographic dataset including first data objects representative of first data from the first data source and at least one geo-spatial reference based on respective location information from the first data source that corresponds to the first data. The system can also generate a vector map data tile layer based on the ontology using the geographic dataset and including vector map data tiles, having map geometry data linked to the first data objects by a geo-spatial reference, and corresponding to a portion of a geographic area represented by the vector map data tile layer. In response to requests from the front-end system application for first data related to a geo-spatial feature, tiles can be provided and first data corresponding to selected geo-spatial references can be displayed.