Multi-person collaborative operation method for geographic information data production and updating

Abstract

The invention discloses a multi-person collaborative operation method for geographic information data production updating, and provides an off-line collaborative operation method which adopts a basic thought that mass data is subjected to centralized management in a server and multi-person off-line collaborative operation editing in a client. Through the technical methods of version management, updating process data redundancy storage, conflict detection, conflict processing and the like, multi-person off-line collaborative operation oriented to massive geographic information data is realized, so the editing efficiency is irrelevant to the server data volume and the number of collaborative operation personnel, and the operation efficiency is improved. Through a version management and updating process data redundancy storage method, the editing process backtracking of specified elements can be supported, and export of incremental updating data between any version database and any two specified versions is realized. The multi-person collaborative operation requirement for mass data can be met, the investment of operators can be flexibly increased at low cost according to the project requirement, and it is guaranteed that the project is smoothly completed on schedule.

Description

technical field [0001] The invention relates to the geographic information industry, and is mainly aimed at the technical field of geographic information data production and updating in a large area, with a large amount of data, requiring multiple people to work at the same time, and specifically relates to a multi-person collaborative operation method for geographic information data production and updating. Background technique [0002] The existing traditional basic surveying and mapping update technology needs to physically cut the cross-frame elements, which increases the tedious work of joining the data frame after the production update, and the efficiency is low; the online collaborative update technology of ArcGIS is limited by the data volume, Constrained by many conditions such as the number of concurrent users and version editing time, the management of massive data, the increase of concurrent users (more than 3 people), the increase of version editing time, etc., w...

AI Technical Summary

Problems solved by technology

[0002] The existing traditional basic surveying and mapping update technology needs to physically cut the cross-frame elements, which increases the tedious work of joining the data frame after the production update, and the efficiency is low; the online collaborative update technology of ArcGIS is limited by the data volume, Constrained by many conditions such as the number of concurrent users and version editing time, the management of massive data, the increase of concurrent users (more than 3 people), the increase of version editing time, etc., will lead to slow response speed, refresh waiting, or even freeze , which seriously affects the work efficiency

[0003] The traditional framing operation technical scheme needs to physically cut the data according to the standard framing. A large number of complete geographic element objects are divided into multiple parts and distributed to different operators for processing. Operators can only pay attention to parts during the production process. Information, and after the framing data production update is completed, complex border work will be carried out, involving geometric accuracy, graphic articulation, attribute correction, etc., resulting in low operation efficiency and hidden quality risks; the space based on the ArcSDE version control strategy Data online collaborative update technology can enable multiple people to edit the same data at the same time, without the need for slicing and border work, which improves the efficiency of data production to a certain extent, but this technical solution is highly dependent on the performance of the central server and the local area network environment. Version registration, role and user permission configuration, in the face of massive data, multi-user concurrency, etc., may easily cause slow response of the server, or even freeze phenomenon. Every time one person’s job is added or a certain amount of data is added, the bottleneck phenomenon is very obvious and cannot be satisfied. Large-scale operation requirements in actual production

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