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Concept help - Quality Statement

A Data Quality Statement records any known issues that may be related to a data asset. A Data Quality Statement assesses data against seven key factors: Institutional Environment, Relevance, Timeliness, Accuracy, Coherence, Interpretability & Accessibility.
<div class="well"> <header>The ABS Data Quality Framework</header>

The ABS Data Quality Framework (ABS DQF) provides the standards for assessing and reporting on the quality of statistical information. It can also assist you with the development of statistical collections to produce high quality outputs.

The ABS DQF is based on the Statistics Canada Quality Assurance Framework (PDF, 178.05 KB) and the European Statistics Code of Practice (PDF, 1.09 MB). It consists of seven dimensions of quality: institutional environment, relevance, timeliness, accuracy, coherence, interpretability, and accessibility.

</div> <cite> Based on Australian Bureau of Statistics ABS Data Quality Statement Checklist </cite>

Fields available on this metadata type

Field ISO definition
Name The primary name used for human identification purposes.
Definition Representation of a concept by a descriptive statement which serves to differentiate it from related concepts. (3.2.39)
Version Unique version identifier of this metadata item.
References Significant documents that contributed to the development of the metadata item which were not the direct source for the metadata content.
Origin The source (e.g. document, project, discipline or model) for the item (8.1.2.2.3.5)
Comments Descriptive comments about the metadata item (8.1.2.2.3.4)
Deleted The date after which the item has been soft deleted and is no longer visible in the registry
Institutional Environment A description of the origin of the data collection and what arrangements or governance is in place. This information gives context about the reliability and validity of the data set.
Timeliness How long ago was the information collected? If the data is old, is it part of a time series where changes over time can be viewed. Is there a lag between when the data was received and when it was published?
Accessibility Is the information easily obtained? Is it available through a web site or is it obtainable by request? If permission is required to access the data is it clear how to obtain these permissions?
Interpretability Is there an abundance of information available about this subject? Is there sufficient metadata to support the data including concepts and classifications?
Relevance An assessment of whether the collection was fit for purpose. What was the target population and whether the collection is representative of that population? Was the response to the collection of the data sufficient to provide reliable information?
Accuracy Whether the data describes what was to be measured correctly. The types and number of errors in the data should be considered when rating this category. If it is known that there were errors in the response or sample or other errors in accuracy of the data, it should be noted.
Coherence Does this collection adhere to known standards about the subject? Is the methodology known and understood widely?

Custom Fields

Field Short definition Long definition
Example field

Official Definition

A Data Quality Statement is a presentation of information about the quality of a statistical collection or product using the Data Quality Framework. These may also be referred to as Data Quality Declarations. ABS Data Quality Statement Checklist