Geographical Information Systems

Geog 481/506                                                                                                  Tu Th 3:30-4:50pm
Fall 2011                                                                                                          Fillmore 170

Instructor: Ling Bian                                                                                          LabA: Tue:   5-6:20pm, W145, Chunyuan Diao
Office: 120 Wilkeson                                                                                        LabB: Thur:  6:30-7:50pm, W145, Tong Sun
Office hours: Tu Th 2-3pm  or by appt.                                                             LabC: Fri:  10-11:20am, W145, Tong Sun

Data Quality

1. Necessity
            Practical
            Legal
           Theoretical

            Accuracy: A measure of how close data match the true value or descriptions.

            Precision: A measure of how exact data are measured and stored.
            Error: The deviation between the measured value and the true value of a feature.
            Uncertainty: A lack of confidence in the use of data due to the incomplete of knowledge.

2. Sources of error

(1) Inherent errors
    Errors contained in source data, and they cannot be eliminated
            Map creation
                    Projection, generalization, etc.

            Map availability

                    Age of map, area coverage, map scale, map format, map accuracy,
                    and map accessibility, etc.

(2) Operational errors

            Errors introduced during data entry and manipulation.
            Inherent errors may be enhanced by operational errors.
            Data entry
            Data storage
                     Numeric precision
                     Locational precision

            Data manipulation

                Sampling/interpolation
                Conversion
                Overlay

                Output accuracy can only be as accurate as the least accurate individual layer

3. Data quality assessment

            Data quality: "Fitness for use"

            Data quality assessment: "Truth in labeling"

            It is data producer's responsibility to provide detailed information about the data.
            It is users' responsibility to make their judgment of "fitness for use".

            Metadata - data about data

            Federal Geographic Data Committee (FGDC)
                    Content Standard for Digital Geospatial Metadata

        U.S. National Committee for Digital Cartographic Data Standards (NCDCDS):

            Components of data quality
                    Positional accuracy:
                        Closeness of coordinates to the true position

                    Attribute accuracy:

                        Closeness of attribute values to their true value
 
                    Logical consistence:
                        How well relation among data elements are maintained

                    Completeness:

                        The proportion of data available for the area of interest

                    Lineage:

                        Data sources and the process steps used to produce the data

4. Reading: Chpt 4