Temporal Quality

Definition 

Changes made to a dataset over time are recorded and repeatable. High temporal quality consists of a detailed, consistent version history that is discoverable in the metadata of subsequent versions of a dataset.

Checks 

Temporal accuracy 
Temporal consistency
Temporal validity

Pass Requirements 

Temporal accuracy: Ensure time stamps are included in the metadata (UTC time) so users can identify when the dataset version was created. This can help identify the latest version of a dataset.
Temporal consistency: Ensure a standardised file naming convention and metadata structure is followed so the dataset version is easily understood.
Temporal validity: Ensure a detailed work flow is included in the metadata so users can identify the order of changes made to the data and are able to replicate the process.

Examples

Description  

4887 Apollo Marine Park 20200421 and 4887 Apollo Marine Park 2020-2021 (clearing house). 

Test results  

Temporal accuracy: Time stamps are in different formats in the metadata.
Temporal consistency: File name formats are different between the two versions.
Temporal validity: Processing strategy was not carried over to the new version.

Pass 

No (we acknowledge this is a fault due to the data submission requirements evolving during the time of submission).

Explanation  

This datasets fails checks 1, 2 and 3 as listed above.

Description  

Beagle Marine Park bathymetry survey 2018 (20180011S)

Test results  

Temporal accuracy: Time stamps are in consistent formats in the metadata.
Temporal consistency: File name formats are consistent.

Pass 

Yes

Explanation  

This dataset passes all checks listed above.