Difference between revisions of "ISO 19157:2013 Geographic information - Data quality"

From ICA Wiki
Jump to navigation Jump to search
Line 61: Line 61:
  
 
==Implementation guidelines==
 
==Implementation guidelines==
−
While ISO 19131:2007 does include annexes with UML class diagrams and data dictionaries as tables (as is done in ISO 19115:2003), it is probably still necessary for the user to consult ISO 19115:2003 when using ISO 19131:2007, as ISO 19115:2003 has more details about the metadata (and hence, product specification) concepts, elements and entities.
+
ISO 19157:2013 cancels and replaces ISO/TS 19138:2006, ISO 19114:2003 and ISO 19113:2002. According to ISO 19157:2013, data quality comprises six elements: completeness, thematic accuracy, logical consistency, temporal quality, positional accuracy and usability. Each element is comprised of a number of sub-elements, for example, completeness (commission and omission), logical consistency (conceptual, domain, format, topological), etc. These elements are used to describe data quality, i.e. how well a specific dataset meets the criteria for the different elements set forth in its product specification or user requirements. Evaluation against the criteria is done either quantitatively or subjectively (non-quantitatively). The latter case applies if a detailed data product specification does not exist or if the data product specification lacks quantitative measures and descriptors. Three metaquality elements – confidence, ‘representativity’ and homogeneity – provide quantitative and qualitative statements about the evaluation against the criteria and its result.
−
ISO 19131:2007 specifies that a data product specification shall describe the following aspects of the product:
 
  
−
# Overview: source and provenance of the specification, relevant terminology and an informal description of the required product, such as the dataset content, spatial and temporal extents, purpose, sources, production processes and maintenance.
+
Quality information can be provided for different units of data, e.g. a dataset series, a dataset or a subset of a dataset with common characteristics. A data quality unit comprises of a scope and data quality elements. The scope specifies the extent, spatial and/or temporal and/or common characteristic(s) of the unit for which the quality information is provided.  
−
# Specification scopes: the scope of the required product, in terms of spatial and temporal extent, feature types, property types, property values, spatial representation, product hierarchy and partitioning (e.g. between the dynamic and static sorts of data in the required product), The concept ‘product hierarchy’ is not defined in the standard, but this applies to each of the partitions of the product being specified, as they can be at different levels: attribute, attribute type, feature, feature type, tile, dataset, series, etc. For each partition, the level code, level name, level description, extent and coverage are to be specified.
 
−
# Data product identification: title, abstract, topic category (one of the pre-defined themes that applies to the required product, such as farming, boundaries, elevation or transportation) and geographic description (actually, spatial extent) shall be provided and alternate title, purpose, spatial representation type (e.g. vector or raster), spatial resolution and supplemental information may be provided.
 
−
# Data content and structure: feature-based, coverage-based or imagery data. The content of a feature-based product shall be described in terms of an application schema (content, structure and constraints applicable) and a feature catalogue (or classification system). The application schema can be very complicated, catering for relationships between feature, property and attribute types, such as feature operations, feature association, inheritance relations and constraints. Imagery data are a form of coverage and a coverage is a sub-type of a feature, which behaves like a function returning one or more feature attribute values for some point within a spatiotemporal domain. A coverage requires an identifier, a description, the type and additional information.
 
−
# Reference systems: the spatial reference system (using coordinates or geographic identifiers) and the temporal reference system.
 
−
# Data quality: the data quality requirements, acceptable conformance quality levels and corresponding data quality measures. In ISO 19131:2007, the data quality requirements are specified in terms of ISO 19113 and ISO/TS 19138, but these have now been revised by ISO 19157:2013 (described in 10.7.3).
 
−
# Data capture: an optional specification of the sources and processes that shall or may be used for the data capture.
 
−
# Data maintenance: an optional specification of the principles and criteria to be applied in maintaining the product, such as maintenance and update frequency.
 
−
# Portrayal: an optional specification of the portrayal rules and a set of portrayal specifications, for specifying how the data may be represented graphically. This could be particularly important for a web service, for example.
 
−
# Data product delivery: delivery format (e.g. transfer standard) and delivery medium (e.g. CD-ROM). The delivery format details may include the name and version of the format; subset, profile or product specification; structure of the delivery file; language(s) and character encoding. The delivery medium details may include units of delivery (how the data are arranged on the medium), estimated sizes, name of the delivery medium and other delivery information.
 
−
# Additional information: a catchall for anything else to be specified for the product, such as constraint information regarding access and use.
 
−
# Metadata: the metadata that shall be provided with the product, defined in terms of ISO 19115:2003.
 
  
−
With the publication of ISO 19117:2012, Geographic information – Portrayal, ISO 19157:2013, Geographic information – Data quality, and ISO 19115-1:2014, Geographic information – Metadata – Part 1: Fundamentals, ISO 19131:2007 is due to be revised.
+
In ISO 19157:2013, quality related information provided by purpose, usage and lineage of geographic data conforms to ISO 19115-1:2014 (described in chapter 11).
 +
 
 +
ISO 19157:2013 specifies four conformance classes, i.e. the standard can be implemented for four different quality aspects of geo-spatial datasets, each briefly described below.
 +
# Implementing a data quality evaluation process conforming to ISO 19157:2013
 +
A data quality evaluation process conforming to ISO 19157:2013 comprises of four steps:
 +
* Step 1 - Specify the data quality units to be evaluated. Study the data product specification to identify applicable data quality units and their scope. For each data quality unit, identify the applicable data quality element(s). See example in Table 10.25.
 +
* Step 2 - Specify the data quality measures to be used to describe quality of each data quality element of a data quality unit. The requirements in the data product specification provide guidance on applicable data quality measures. See example in Table 10.26. The data quality measures in the table are from the list of standardized data quality measures in ISO 19157:2013. It is also possible to describe user-defined quality measures, see further below, and to maintain a collection of such measures in a catalogue or register.
 +
* Step 3 - Specify the data quality evaluation procedures, i.e. the evaluation method(s) to be applied. The method can be direct (based on inspection of the items in the dataset) or indirect (based on external knowledge, such as lineage metadata). Direct evaluation is further classified by the source against which the evaluation is done: internal if only the data in the dataset is evaluated or external if there is reference to external data (e.g. satellite imagery or ground truth). ISO 19157:2013 includes guidance on how to sample data for evaluation.
 +
* Step 4 - Determine the output of the data quality evaluation, i.e. perform the data quality evaluation described in Steps 1-3 above. Additional results may be produced by aggregating or by deriving from existing results without carrying out a new evaluation. How to report the results of the data quality evaluation is described elsewhere in this chapter.

Revision as of 11:05, 4 May 2016

Overview

Full name ISO 19157:2013, Geographic information – Data quality.
Version Edition 1
Amendments None
Corrigenda None
Published by ISO/TC 211
Languages English, French
Online overview https://www.iso.org/obp/ui/#iso:std:iso:19157:ed-1:v1:en
Type of standard ISO International Standard

Meta level.

Related standard(s) ISO 19115-1:2013, Geographic information – Metadata – Part 1: Fundamentals

ISO 19115-2:2009, Geographic information – Metadata – Part 2: Extensions for imagery and gridded data ISO 19158:2012, Geographic information – Quality assurance of data supply

Application The standard specifies the description, evaluation and reporting of the quality of geographic data.
Conformance

classes

Data quality evaluation process

Data quality metadata Standalone quality report Data quality measure

Scope

ISO 19157:2013 establishes the principles for describing the quality for geographic data. It defines components for describing data quality; specifies components and content structure of a register for data quality measures; describes general procedures for evaluating the quality of geographic data; and establishes principles for reporting data quality.

The standard also defines a set of data quality measures for use in evaluating and reporting data quality. It is applicable to data producers providing quality information to describe and assess how well a dataset conforms to its product specification and to data users attempting to determine whether or not specific geographic data are of sufficient quality for their particular application.

The standard does not attempt to define minimum acceptable levels of quality for geographic data.

Implementation benefits

ISO 19157:2013 provides a standard way for describing the quality of geographic data. Such descriptions are useful when a producer has to evaluate how well a dataset meets the criteria described in its product specification. For example, if the producer outsourced the acquisition of the data, ISO 19157:2013 could be used to evaluate and describe the quality of the received data during acceptance testing.

Geographic data are increasingly shared and exchanged. As a result, geographic data are often used for purposes that differ from the purpose for which it was originally captured. Complete descriptions of the quality of a dataset encourage and facilitate the sharing, interchange and use of appropriate datasets.

Another benefit of implementing ISO 19157:2013 is that the quality information could assist a user who has to decide whether a specific dataset is appropriate for an intended use or application. If the user has to decide between two or more datasets, standardized quality descriptions simplify comparing the datasets. If ISO 19157:2013 is implemented, quality reports are expressed in a comparable way and there is a common understanding of the quality measures that have been used. A project to develop an XML of ISO 19157:2013 has begun.

Implementation guidelines

ISO 19157:2013 cancels and replaces ISO/TS 19138:2006, ISO 19114:2003 and ISO 19113:2002. According to ISO 19157:2013, data quality comprises six elements: completeness, thematic accuracy, logical consistency, temporal quality, positional accuracy and usability. Each element is comprised of a number of sub-elements, for example, completeness (commission and omission), logical consistency (conceptual, domain, format, topological), etc. These elements are used to describe data quality, i.e. how well a specific dataset meets the criteria for the different elements set forth in its product specification or user requirements. Evaluation against the criteria is done either quantitatively or subjectively (non-quantitatively). The latter case applies if a detailed data product specification does not exist or if the data product specification lacks quantitative measures and descriptors. Three metaquality elements – confidence, ‘representativity’ and homogeneity – provide quantitative and qualitative statements about the evaluation against the criteria and its result.

Quality information can be provided for different units of data, e.g. a dataset series, a dataset or a subset of a dataset with common characteristics. A data quality unit comprises of a scope and data quality elements. The scope specifies the extent, spatial and/or temporal and/or common characteristic(s) of the unit for which the quality information is provided.

In ISO 19157:2013, quality related information provided by purpose, usage and lineage of geographic data conforms to ISO 19115-1:2014 (described in chapter 11).

ISO 19157:2013 specifies four conformance classes, i.e. the standard can be implemented for four different quality aspects of geo-spatial datasets, each briefly described below.

  1. Implementing a data quality evaluation process conforming to ISO 19157:2013

A data quality evaluation process conforming to ISO 19157:2013 comprises of four steps:

  • Step 1 - Specify the data quality units to be evaluated. Study the data product specification to identify applicable data quality units and their scope. For each data quality unit, identify the applicable data quality element(s). See example in Table 10.25.
  • Step 2 - Specify the data quality measures to be used to describe quality of each data quality element of a data quality unit. The requirements in the data product specification provide guidance on applicable data quality measures. See example in Table 10.26. The data quality measures in the table are from the list of standardized data quality measures in ISO 19157:2013. It is also possible to describe user-defined quality measures, see further below, and to maintain a collection of such measures in a catalogue or register.
  • Step 3 - Specify the data quality evaluation procedures, i.e. the evaluation method(s) to be applied. The method can be direct (based on inspection of the items in the dataset) or indirect (based on external knowledge, such as lineage metadata). Direct evaluation is further classified by the source against which the evaluation is done: internal if only the data in the dataset is evaluated or external if there is reference to external data (e.g. satellite imagery or ground truth). ISO 19157:2013 includes guidance on how to sample data for evaluation.
  • Step 4 - Determine the output of the data quality evaluation, i.e. perform the data quality evaluation described in Steps 1-3 above. Additional results may be produced by aggregating or by deriving from existing results without carrying out a new evaluation. How to report the results of the data quality evaluation is described elsewhere in this chapter.
Retrieved from "http://wiki.icaci.org/index.php?title=ISO_19157:2013_Geographic_information_-_Data_quality&oldid=174"