Data Quality Register

DPI is the registered custodian agency (see glossary) of the data

The data aligns with the Data Quality Framework, including:

• Legislation
• Policies
• Information Asset Governance
• Standards
• Data Management Plans

The following governance roles and responsibilities for this asset are clearly assigned:

• Information Asset Owner (see glossary)
• Information Asset Custodian (see glossary)
• Data Steward (see glossary)

Data collection is authorised by law, regulation or agreement

The Custodial agency has no commercial interest or conflict of interest (see glossary) in the data

Data has been subject to a data assurance process (For example: Checking for errors at each stage of data collection and processing, or verifying data entry and making corrections if necessary.)

Data is revised and the revision is publicised if errors are identified

The impact of any adjustments or other changes are identified in caveats attached to asset (see glossary)

There are no known gaps in the data or if there are gaps (for example: non-responses, missing records, data not collected), they have been identified in caveats attached to asset (see glossary)

Any factors impacting validity are identified in caveats attached to asset (see glossary)

Standard concepts, classifications and metadata standards are used

Elements within the data can be meaningfully compared or combined with data from other sources

This data is generally consistent with similar or related data sources from the same discipline

The data can be analysed over time

This data is consistent with previous releases if part of a collection

A data dictionary is available to explain the meaning of data elements, their origin, format and relationships

Information is available about the sources and methods of data collection (e.g. instruments, forms, instructions).

Information is available to help users evaluate the accuracy of the data and any level of error

Information is available to explain concepts, help users correctly interpret the data and understand how it can be used

Information is available to explain ambiguous or technical terms used in the data

Data is available online with an open licence

Data is available in machine-processable, structured form (e.g. CSV format instead of an image scan of a table)

Data is available in a non-proprietary format (e.g. CSV, XML)

Data is described using open standards (e.g. RDF, SPARQL) and persistent identifiers (URIs or DOIs)

Data is linked to other data, to provide context (e.g. employee ID is linked to employee name or species name is linked to genus)