T/GDSTD 004-2025 Active Group standards

T/GDSTD 004-2025 Technical Specifications for Data Governance of State-Owned Construction Land Supply

T/GDSTD 004-2025 Land supply data governance technical specification for state-owned construction land

Publish Date: 2025-05-20 Implement Date: 2025-05-20 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

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Basic Information

Standard Code: T/GDSTD 004-2025

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: -

ICS Name: Comprehensive Application of Information Technology

Publish Date: 2025-05-20

Implement Date: 2025-05-20

Scope

Main Technical Content: The main content of this standard includes the governance of state-owned construction land supply data, the governance process, the content of the post-governance results, and the requirements for data submission. This standard applies to the governance of state-owned construction land supply data in the Guangdong Province Natural Resources Market and Development Utilization Monitoring and Supervision System. 1. Data Governance Content The object of data governance for state-owned construction land supply data is the recorded data of construction land projects supplied in the Guangdong Province Natural Resources Market and Development Utilization Monitoring and Supervision System, including data on state-owned construction land supplied through methods such as allocation, transfer, and leasing. The scope of state-owned construction land supply data to be governed includes graphic, attribute, and archival data. 2. Data Governance Process The process of data governance for state-owned construction land supply data includes the following steps: - Data collection: Collect data such as archival materials, relevant business results, and auxiliary analysis data for state-owned construction land supply. The collected data should ensure accuracy, completeness, security, and compliance. - Data analysis: Conduct graphic and attribute problem analysis on the collected data. - Data processing: Address issues such as missing graphics, graphic topology, inconsistent graphic and attribute areas, graphic overlapping, and graphics exceeding administrative boundaries (including zero-meter lines), as well as missing attribute information and logical errors in attribute data. - Data quality inspection: Conduct basic inspections of spatial data, standard compliance checks for attribute data, spatial graphic data checks, consistency between graphics and attributes, and logical checks on the data. - Data storage: Organize spatial elements into su