Every dataset in SEED includes a Data Quality Statement. The Data Quality Statement is available under the 'Data Quality Statement' heading when you view the dataset details.
What is data quality?
‘Data quality’ is determined by whether the data is suitable for its original intended use. This is generally referred to as being 'fit-for-purpose'. Data is of sufficient quality if it fulfils its intended use (or re-use) in operations, decision making or planning.
What is the Data Quality Statement?
The Data Quality statement helps a user understand how a particular dataset could be used, and whether the dataset can be compared with other, similar datasets. It provides a description of the characteristics of the data to help the user decide whether the data will be fit for the user’s specific purpose.
Users can make different assessments about the fitness of the same data, depending on the way they plan to use the data.
How is the Data Quality Statement prepared?
The Data Quality statement is prepared by the data custodian (provider of the dataset), using a reporting questionnaire that has been developed in accordance with the NSW Government Standard for Data Quality Reporting.
The reporting questionnaire assesses the data against a prescribed set of five data quality criteria:
• Institutional Environment
For each question: “yes” = 1 point; “no” = 0 points.
Dimensions with four or five points receive a star.
What is the data quality rating?
A star rating system is included in the Data Quality Statement to quickly indicate the dataset’s comparative strengths and weaknesses against the prescribed criteria.
To achieve a star for a particular criterion, a dataset must achieve at least four out of a possible five points.
The data quality rating for the dataset is displayed on the dataset page.
Be aware that the data quality rating needs to be interpreted with some care. For example:
• A dataset which is rated as “Good” for every data quality criterion will have zero stars
• A dataset which is rated as “Poor” for two criteria and “Very Good” for three criteria, will have 3 stars.
Whilst the data quality rating provides a quick indication of a dataset’s strengths, users should refer to the more comprehensive Data Quality Statement for more detailed information. Users may make different assessments about the fitness of the same data, depending on the way they plan to use the data