Interpretability is the sixth dimension of quality in the ABS DQF. Interpretability refers to the availability of information to help provide insight into the data. Information available which could assist interpretation may include the variables used, the availability of metadata, including concepts, classifications, and measures of accuracy. Interpretability is an important component of quality as it enables the information to be understood and utilised appropriately.
The Interpretability of a statistical collection, product or release can be evaluated by considering two key aspects:
- Presentation of the information: the form of presentation and the use of analytical summaries to help draw out the key message of the data
- Availability of information regarding the data: the availability of key material to support correct interpretation, such as concepts, sources and methods; manuals and user guides; and measures of accuracy of data.
To assist in evaluating the Interpretability dimension of a dataset or a statistical product, we provide some suggestions of questions which might be asked below.
Suggested questions to assess Interpretability
- Are terms used in the statistical release or dataset which are ambiguous or likely to be confusing for a user?
- To what extent can a user of the release or dataset find supporting information about the data to enable improved interpretation?
- Are there information papers or articles available to help provide more insight into the concept(s) measured?
- Is there information available to help the user gauge the potential magnitude of error in the data?