Key terms and concepts

Here are explanations of terms and concepts that are often requested and are important in working with geodata. For a complete list of terms, see the national term database for geodata.

Term database and tutorial

National term database for geodata (in swedish, new window)

Quality terms are described in the web-based guide (in swedish, new window) to the standard Geographic information - Data quality (ISO 19157: 2013).

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Timeliness refers to the time when the object was last, through control, found to be correctly reported.

To establish that an object is current, it is not enough to look at it dates set when the object is produced, a building may have been built and entered in the data set many years ago, but it is still correct and valid.

What is interesting for the user is to know when the data was last checked .

Quality concept

Quality is described as the degree of agreement between the user's needs and the product's characteristics.

The general The term quality is detailed for different areas. The terms data quality and geodata quality are used in geodata. In text, the three terms are often used synonymously, and it is clear from the context, what type of quality is meant.

Definition of quality is made in the standard Management system for quality, ISO 9000. The 9000 series has been developed to help organizations of all types to implement and manage management systems to achieve quality in their processes and products.

Requirements for geodata quality are specified and evaluated using categories of quality characteristics, which are divided into the two groups technical and functional. The technical quality is a description of the properties of the data set, while the functional one touches on how the data set is suitable for use in different applications.

For the description of the quality of a spatial data set, the model documented in the metadata standard SS-EN-ISO 19115 is used It includes models for reporting:

  • quality requirements
  • results and documentation of the evaluation of the fulfillment of requirements
  • history of origin
  • purpose
  • Usage
  • Usability

Based on the information, a user can assess the usability for their needs.

To report Geodata quality needs several characteristics to be described, these are called categories of quality characteristics. They are divided into two technical and functional groups. The description of them is included in each standard, Metadata and Data Quality respectively. In the standard Specification of data sets SS-EN-ISO 19131, they are applied and the result is reported according to the metadata standard.

Functional quality properties are divided into:

  • use
  • origin history
  • purpose

These are described in the Metadata standard SS-EN-ISO 19115-1.

Technical quality requirements for geodata are divided into:

  • completeness
  • usability
  • positional accuracy
  • thematic accuracy
  • temporal accuracy
  • logical consistency.

The model for the technical quality requirements is defined in the standard Data quality SS-EN-ISO 19157, which also includes the model for evaluating the properties. The technical categories of quality characteristics have a finer division called quality characteristics.

Timeliness is used to describe how data has aged, and is seen as an important quality aspect, but is not defined in any standard. Usually indicates when the data was last found to be accurate. For data sets that are continuously updated, a description of the lead time is important for the assessment of timeliness.

In the technical specification Quality assurance of data supply, SIS-ISO / TS 19158 uses, in addition to data quality according to SS-EN-ISO 19157, also scope, schedule and cost as categories of quality characteristics in quality assurance of producers for geodata collection.

More about geodata quality can be read in:

Accuracy and uncertainty

The concepts of accuracy and uncertainty occur in quality contexts, highlighting the difference and why both concepts are needed.

Accuracy

- is the correspondence between a measured value and a true value. (Source: ISO 3534-2 Statistics - Vocabulary and symbols) , Situation accuracy then becomes accuracy one in the position indication. The term is used in all geodata standards within the ISO 19100 series (Source: ISO 19157: 2013, Geographic information - Data quality).

Uncertainty

- reflects vision that conclusions are drawn from measurements calculated using statistical methods, without referring to true value. This is also described in the ISO 19100 series, as well as in the standard Guide to the Expression of Uncertainty in Measurement (GUM) (JCGM 100: 2008).

Conclusions

  1. The concepts bottom out in different basic views about true values resp. uncertainties. In practice, there is no difference.
  2. In ISO 19100, the terms are used so that accuracy is an overall classification for a "type" of quality. To be consistent with other spatial data standards, it is recommended to follow this terminology. Uncertainty is used here as a measure.
  3. It is important to be clear with which concepts you use and why.
Fictitious examples
Types of quality Position accuracy Completeness
Subtype Absolute accuracy Lack
Dimensions Mean value for position uncertainty (one (distance measure calculated according to statistical methods) Percentage missing objects (in percent)
Ex. on quality requirements "None of the nodes in the data set should have a position uncertainty greater than 1 m" "The data set must have a max. 10% fewer houses than reality"
Ex. on
reporting of quality
measurement
"Meets "alternatively
"0.85 m"
"Does not meet" alternatively
"12%"

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