Objectives

• Differentiate accuracy, precision, error, and uncertainty.

• Discuss the dimensions of geographic data quality.

• Discuss how to compute RMSE for positional accuracy.

• Describe why data standards are beneficial

• Key terms: metadata

•Accuracy—how close to “true”

•Precision—how exactly measured and stored

•Error—deviation from “true” value

•Uncertainty—lack of confidence due to incomplete knowledge

Inherent = Source

Operational = user

or processing

Semantic DiscrepanciesSemantic Discrepancies

• RMSE = sqrt(average(squared discrepancies))

• x, y, and z (or e)

• p = sqrt(x²+ y²) (Positional)

• Use p and e for map overall

Metadata—Geographic Data Quality

• Lineage

• Positional accuracy

• Attribute accuracy

• Logical consistency

• Completeness

Spatial autocorrelation

Sampling

Standards vs Translators