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Editorial: The Importance of Data Integrity in Spatial Work

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Bill McNeil
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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.

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