Geographic Big Data GIS Technology System

Distributed storage of spatiotemporal big data

● Provide integrated storage and management of data types such as relational, sliced, real-time, unstructured, blockchain, graph data, vector, etc

● Provide storage of graph data based on Nebula Graph database to support geographic knowledge graph services

● Support direct storage of billion level graph data, continuously storing billion level graph data while maintaining high speed

Standardization governance of spatiotemporal big data

● Provide a standard spatiotemporal big data governance process to improve the quality of spatiotemporal big data

● Connect all aspects from spatiotemporal big data collection, spatiotemporal big data governance, spatiotemporal big data analysis to spatiotemporal big data application

● Building a metadata based full lifecycle management system to continuously enhance and explore the value of spatiotemporal big data

Distributed analysis of spatiotemporal big data

● A distributed computing framework based on spatiotemporal big data, providing four major categories of big data services: vector, image, real-time, and text big data

● Provide a distributed geographic processing flow engine, based on a visual modeling environment, to quickly build geographic processing models

● Provide 300+distributed big data analysis operators covering multiple scenarios and fine-grained, allowing for flexible construction of complex business processes

● Support the construction, visualization, querying, and analysis of knowledge graphs

● Added Bayesian training prediction, time series prediction, pipeline leakage calculation, GeoSOT grid partitioning and other operators

● Add GP workflow services such as pipeline status assessment, pipeline leakage location, and mineralization prediction

Visualization and rendering of spatiotemporal big data

● Integrate open source frameworks such as OpenLayers, Leaflet, MapboxGL, Cesium, ThreeJS, as well as visualization libraries such as MapV and Echarts GL

● Optimize the rendering performance of massive vector data, achieve real-time publishing and second level browsing of massive vector data without slicing

● Provide spatial big data visualization technologies such as scatter plot, heatmap, honeycomb plot, grid plot, trajectory plot, O-D plot, flow chart, wind field, etc

● Provide visual representation of knowledge graph