Editorial: The Importance of Data Integrity in Spatial Work

In the rush to adopt new geospatial technologies, it's easy to overlook the fundamentals — data integrity. Without consistent standards, spatial analysis may become unreliable.
What Data Integrity Means
It includes coordinate accuracy, metadata, versioning, and transparent workflow documentation.
Risks of Ignoring Integrity
Errors propagate through projects, damaging credibility.
Data integrity is the foundation of reliable spatial analysis.















