The descriptions of the elements and measures are based on Annex D of ISO/DIS Geographic information Data quality.

Size: px

Start display at page:

Download "The descriptions of the elements and measures are based on Annex D of ISO/DIS Geographic information Data quality."

Jasmin Foster
5 years ago
Views:

1 7 Data quality This chapter includes a description of the data quality elements and sub-elements as well as the corresponding data quality measures that should be used to evaluate and document data quality for s related to the spatial data theme Statistical Units (section 7.1). It may also define requirements or recommendations about the targeted data quality results applicable for s related to the spatial data theme Statistical Units (sections 7.2 and 7.3). In particular, the data quality elements, sub-elements and measures specified in section 7.1 should be used for evaluating and documenting data quality properties and constraints of spatial objects, where such properties or constraints are defined as part of the application schema(s) (see section 5); evaluating and documenting data quality metadata elements of spatial s (see section 8); and/or specifying requirements or recommendations about the targeted data quality results applicable for s related to the spatial data theme Statistical Units (see sections 7.2 and 7.3). The descriptions of the elements and measures are based on Annex D of ISO/DIS Geographic information Data quality. 7.1 s Table 3 lists all data quality elements and sub-elements that are being used in this specification. Data quality information can be evaluated at level of spatial object, spatial object type, or series. The level at which the evaluation is performed is given in the Evaluation Scope column. The measures to be used for each of the listed data quality sub-elements are defined in the following sub-sections. Table 3 s used in the spatial data theme Statistical Units Section Data quality element Data quality sub-element Completeness Commission excess data present in the, as described by the scope Completeness Omission data absent from the, as described by the scope 0 Logical Topological correctness of the explicitly encoded consistency consistency topological characteristics of the Positional accuracy Thematic accuracy Absolute or external accuracy Classification correctness Temporal quality Temporal validity, as described by the scope closeness of reported coordinate values to values accepted as or being true comparison of the classes assigned to features or their attributes to a universe of discourse validity of data specified by the scope with respect to time Evaluation Scope

2 Recommendation 1 Where it is impossible to express the evaluation of a data quality element in a quantitative way, the evaluation of the element should be expressed with a textual statement as a data quality descriptive result Completeness Commission Recommendation 1 Commission should be evaluated and documented using Rate of excess items as specified in the tables below. Rate of excess items Alternative name Completeness Data quality sub-element Commission Data quality basic measure Error rate Number of excess items in the in relation to the number of items that should have been present. Description Parameter Data quality value type Real, percentage, ratio (example: 0,0189 ; 98,11% ; 11:582) Data quality value structure Source reference Example Measure identifier 3 (ISO 19138) Completeness Omission Recommendation 2 Omission should be evaluated and documented using Rate of missing items as specified in the tables below. Rate of missing items Alternative name Completeness Data quality sub-element Omission Data quality basic measure Error rate Number of missing items in the in relation to the number of items that should have been present. Description Parameter Data quality value type Real, percentage, ratio (example: 0,0189 ; 98,11% ; 11:582) Data quality value structure Source reference Example Measure identifier 7 (ISO 19138)

3 7.1.3 Logical Consistency Topological consistency Recommendation 3 Topological consistency should be evaluated and documented using Slivers as specified in the tables below. Alternative name Data quality sub-element Data quality basic measure Description Slivers Slivers Logical consistency Topological consistency Error rate A sliver is an unintended area that occurs when adjacent surfaces are not digitized properly. The borders of the adjacent surfaces may unintentionally gap or overlap by small amounts to cause a topological error. This data quality measure has 2 parameters: maximum sliver area size thickness quotient The thickness quotient shall be a real number between 0 and 1. This quotient is determined by the following formula: T is defined as: T=4π area/perimeter² T values are within [0,1]. 1 correspond a circle, and 0 to a line segment. The thickness quotient is independent of the size of the surface, and the closer the value is to 0, the thinner the selected sliver surfaces shall be. The maximum area determines the upper limit of a sliver. This is to prevent surfaces with sinuous perimeters and large areas from being mistaken as slivers. Data quality value type Integer Source reference Environmental Systems Research Institute, Inc. (ESRI) GIS Data ReViewer 4.2 User Guide

4 Example Measure identifier Positional accuracy Absolute or external accuracy Recommendation 4 Absolute or external accuracy should be evaluated and documented using Positional accuracy as specified in the tables below. Positional accuracy Alternative name - Positional accuracy Data quality sub-element Absolute or external accuracy Data quality basic measure Not applicable mean value of the positional uncertainties for a set of positions where the positional uncertainties are defined as the distance between a measured position and what is considered as the corresponding true position Description For a number of points (N), the measured positions are given as xmi, ymi and zmi coordinates depending on the dimension in which the position of the point is measured. A corresponding set of coordinates, xti, yti and zti, are considered to represent the true positions. The errors are calculated as:

5 The mean positional uncertainties of the horizontal absolute or external positions are then calculated as A criterion for the establishing of correspondence should also be stated (e.g. allowing for correspondence to the closest position, correspondence on vertices or along lines). The criterion/criteria for finding the corresponding points shall be reported with the data quality evaluation result. This data quality measure is different from the standard deviation. Data quality value type Measure Source reference - Example - Measure identifier Thematic accuracy Classification correctness Recommendation 5 Classification correctness should be evaluated and documented using Thematic accuracy as specified in the tables below. Thematic accuracy Alternative name - Thematic accuracy Data quality sub-element Classification correctness Data quality basic measure Error rate Number of incorrectly classified features in relation to the number of features that are supposed to be there Description - Data quality value type real, percentage, ratio Source reference - Example - Measure identifier Temporal quality Temporal validity Recommendation 6 Temporal validity should be evaluated and documented using Temporal accuracy as specified in the tables below. Temporal accuracy Alternative name - Temporal accuracy Data quality sub-element Temporal validity

6 Data quality basic measure Correctness indicator Indication of if an item is conforming to its value domain Description - Data quality value type Boolean (true indicates that an item is conforming to its value domain) Source reference - Example - Measure identifier Minimum data quality requirements No minimum data quality requirements are defined for the spatial data theme Statistical Units. 7.3 Recommendation on data quality No minimum data quality recommendations are defined.

The descriptions of the elements and measures are based on Annex D of ISO/DIS Geographic information Data quality.

The descriptions of the elements and measures are based on Annex D of ISO/DIS Geographic information Data quality. 7 Data quality This chapter includes a description of the data quality elements and sub-elements as well as the corresponding data quality measures that should be used to evaluate and document data quality