Standard
UPDATE AVAILABLE
AS/NZS ISO 19157:2015
[Superseded]Geographic information — Data quality
Adopts ISO19157:2013 to establish the principles for describing the quality of geographic data.
Published: 20/02/2015
Pages: 152
Table of contents
Cited references
Content history
Table of contents
Header
About this publication
Preface
Introduction
1 Scope
2 Conformance
3 Normative references
4 Terms and definitions
5 Abbreviated terms
5.1 Abbreviations
5.2 Package abbreviations
6 Overview of data quality
7 Components of data quality
7.1 Overview of the components
7.2 Data quality unit
7.3 Data quality elements
7.3.1 General
7.3.2 Completeness
7.3.3 Logical consistency
7.3.4 Positional accuracy
7.3.5 Thematic accuracy
7.3.6 Temporal quality
7.3.7 Usability element
7.4 Descriptors of data quality elements
7.4.1 General
7.4.2 Measure
7.4.3 Evaluation method
7.4.4 Result
7.4.4.1 General
7.4.4.2 Quantitative result
7.4.4.3 Conformance result
7.4.4.4 Descriptive result
7.4.4.5 Coverage result
7.5 Metaquality elements
7.6 Descriptors of a metaquality element
8 Data quality measures
8.1 General
8.2 Standardized data quality measures
8.3 User defined data quality measures
8.4 Catalogue of data quality measures
8.5 List of components
8.6 Component details
8.6.1 Measure identifier
8.6.2 Name
8.6.3 Alias
8.6.4 Element name
8.6.5 Basic measure
8.6.6 Definition
8.6.7 Description
8.6.8 Parameter
8.6.9 Value type
8.6.10 Value structure
8.6.11 Source reference
8.6.12 Example
9 Data quality evaluation
9.1 The process for evaluating data quality
9.1.1 Introduction
9.1.2 The process flow
9.1.3 Process steps
9.2 Data quality evaluation methods
9.2.1 Classification of data quality evaluation methods
9.2.2 Direct evaluation
9.2.3 Indirect evaluation
9.3 Aggregation and derivation
10 Data quality reporting
10.1 General
10.2 Particular cases
10.2.1 Reporting aggregation (aggregated results)
10.2.2 Reporting derivation (derived results)
10.2.3 Reference to the original data quality result
Annex A
A.1 Test case identifier: Quality evaluation process
A.2 Test case identifier: Data quality metadata
A.3 Test case identifier: Metadata conformity
A.4 Test case identifier: Standalone quality report
A.5 Test case identifier: Data quality measures
Annex B
B.1 Framework of data quality concepts
B.2 The structure of data sets and components for quality description
B.3 When to use quality evaluation procedures
B.4 Reporting quality information
B.4.1 Why report data quality
B.4.2 When to report quality information
B.4.3 How to report quality information
B.4.3.1 Hierarchy principle
B.4.3.2 Metadata and standalone quality report
B.4.3.2.1 General
B.4.3.2.2 Reporting quality information as metadata
B.4.3.2.3 Reporting quality information within a standalone quality report
Annex C
C.1 Data dictionary overview
C.1.1 Introduction
C.1.2 Name/role name
C.1.3 Definition
C.1.4 Obligation/Condition
C.1.4.1 General
C.1.4.2 Mandatory (M):
C.1.4.3 Conditional (C):
C.1.4.4 Optional (O):
C.1.5 Maximum occurrence
C.1.6 Data type
C.1.7 Domain
C.2 Data quality package data dictionary
C.2.1 Data quality
C.2.1.1 General
C.2.1.2 Data quality element
C.2.1.3 Measure reference
C.2.1.4 Data quality evaluation
C.2.1.5 Data quality result
C.2.1.6 Standalone quality report information
C.2.2 Data quality measure
C.2.2.1 General
C.2.2.2 Data quality measures
C.2.2.3 Data quality basic measure
C.2.2.4 Data quality parameter
C.2.2.5 Data quality measure description
C.2.2.6 Data quality measure source reference
C.3 Code lists
C.3.1 Introduction
C.3.2 Evaluation method type
C.3.3 Value structure
Annex D
D.1 Introduction
D.2 Completeness
D.2.1 Commission
D.2.2 Omission
D.3 Logical consistency
D.3.1 Conceptual consistency
D.3.2 Domain consistency
D.3.3 Format consistency
D.3.4 Topological consistency
D.4 Positional accuracy
D.4.1 Absolute or external accuracy
D.4.1.1 General measures for positional uncertainties
D.4.1.2 Vertical positional uncertainties
D.4.1.3 Horizontal positional uncertainties
D.4.2 Relative or internal accuracy
D.4.3 Gridded data positional accuracy
D.5 Temporal quality
D.5.1 Accuracy of a time measurement
D.5.2 Temporal consistency
D.5.3 Temporal validity
D.6 Thematic accuracy
D.6.1 Classification correctness
D.6.2 Non-quantitative attribute correctness
D.6.3 Quantitative attribute accuracy
D.7 Aggregation Measures
Annex E
E.1 Introduction
E.2 Data set description
E.2.1 Data product specification
E.2.1.1 General
E.2.1.2 Feature Types
E.2.1.3 Rules
E.2.1.4 Quality requirements
E.2.2 Representation of the real world, the universe of discourse and the data set
E.3 Quality evaluation process
E.3.1 Specify data quality unit(s)
E.3.2 Specify data quality measures
E.3.3 Specify data quality evaluation procedures
E.3.4 Determine the output of the data quality evaluation (Result)
E.3.4.1 Identification of errors
E.3.4.2 Logical consistency
E.3.4.3 Completeness
E.3.4.3.1 General
E.3.4.3.2 Quantitative result
E.3.4.3.3 Derived conformance result
E.3.4.3.4 Aggregated conformance result
E.3.4.4 Thematic accuracy - classification correctness
E.3.4.4.1 General
E.3.4.4.2 Quantitative result
E.3.4.4.3 Derived conformance result
E.3.4.4.4 Aggregated conformance result
E.3.4.5 Thematic accuracy - quantitative attribute accuracy
E.3.4.5.1 General
E.3.4.5.2 Quantitative result
E.3.4.5.3 Derived conformance result
E.3.4.6 Usability - aggregated conformance to data product specification
E.4 Reporting data quality
E.4.1 Reporting as metadata
E.4.1.1 General
E.4.1.2 Reporting commission
E.4.1.3 Reporting classification correctness
E.4.1.4 Reporting conformance to the data product specification using Usability
E.4.2 Reporting in a standalone quality report
E.5 Additional examples
E.5.1 General
E.5.2 Reporting descriptive results as metadata
E.5.3 Reporting metaquality as metadata
E.5.4 How to report sampling procedure
Annex F
F.1 Introduction
F.2 Lot and item
F.3 Sample size
F.4 Sampling strategies
F.4.1 Introduction
F.4.2 Probabilistic versus judgemental sampling
F.4.2.1 Differences
F.4.2.2 Simple random sampling
F.4.2.3 Stratified random sampling
F.4.2.4 Semi-random sampling
F.4.3 Feature-guided versus area-guided sampling
F.4.3.1 Feature-guided sampling (non-spatial sampling)
F.4.3.2 Area-guided sampling (spatial sampling)
F.5 Probability-based sampling
F.5.1 General considerations
F.5.2 Existing standard for inspection by sampling
F.5.2.1 General
F.5.2.2 Useful tables based on these standards - sample size and rejection limits
F.5.2.2.1 General
F.5.2.2.2 Evaluating conforming/non-conforming items with samples
F.5.2.2.3 Standard deviation
F.5.3 Sampling process
F.5.3.1 Define items
F.5.3.2 Define data quality scopes of a data set to be inspected
F.5.3.3 Divide the data quality scope into lots
F.5.3.4 Divide the lot into sampling units
F.5.3.5 Select sampling units by simple random sampling for inspection
F.5.3.6 Inspection of selected sampling units
Annex G
G.1 Purpose of data quality basic measures
G.2 Counting-related data quality basic measures
G.3 Uncertainty-related data quality basic measures
G.3.1 General
G.3.2 One-dimensional random variable, Ζ
G.3.3 Two-dimensional random variable Χ and Υ
G.3.4 Three-dimensional random variable Χ, Υ, Ζ
Annex H
H.1 Introduction
H.2 Storage of data quality measures
H.2.1 General
H.2.2 Catalogue of data quality measures
H.2.3 Register of data quality measures
Annex I
I.1 Overview
I.2 Data quality element categories
I.2.1 General
I.2.2 Other candidates
I.2.3 Ordering in data quality evaluation
I.3 The relationships between the data quality elements
I.3.1 General
I.3.2 Data quality elements related to missing attribute values
I.3.3 Relationships between the different aspects of accuracy
I.3.4 Dependency between completeness and accuracy
I.4 Data quality elements - example of use
I.4.1 Completeness
I.4.1.1 General
I.4.1.2 Commission - excess data present in a data set
I.4.1.3 Omission - data absent from a data set
I.4.2 Logical consistency
I.4.2.1 General
I.4.2.2 Conceptual consistency - adherence to rules of the conceptual schema
I.4.2.3 Domain consistency - adherence of values to the value domains
I.4.2.4 Format consistency - degree to which data are stored in accordance with the physical structure of the data set
I.4.2.5 Topological consistency - correctness of the explicitly encoded topological characteristics of a data set
I.4.3 Positional accuracy
I.4.4 Temporal quality
I.4.4.1 General
I.4.4.2 Accuracy of a time measurement - closeness of reported time measurements to values accepted as or known to be true
I.4.4.3 Temporal consistency - correctness of the order of events
I.4.4.4 Temporal validity - validity of data with respect to time
I.4.5 Thematic accuracy
I.4.5.1 General
I.4.5.2 Classification correctness - comparison of the classes assigned to features or their attributes to a universe of discourse (e.g. ground truth or reference data set)
I.5 Discussions on difficult cases
I.5.1 Relation between misclassification and completeness at feature type level
I.5.2 Quality elements related to unique identifiers
Annex J
J.1 Introduction
J.2 100 % pass/fail
J.3 Weighted pass/fail
J.4 Maximum/minimum value
Bibliography
AMENDMENT 1: Describing data quality using coverages
Amendment control sheet
Cited references in this standard
[Superseded]
Geographic information — Metadata — Part 2: Extensions for imagery and gridded data
Content history
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