12 - Ontology Data Lifecycle: Data Health

Tabular Foundry datasets can be synchronized to the Ontology's object storage backend, which translates the dataset's rows and columns into objects, properties, and links. As an object type's backing dataset updates, the object type's data in the Ontology automatically updates, too. Since Ontology elements rely on accurate and timely backing dataset builds, you'll use methods similar to those used for tabular data (described in the earlier lessons in the "Tabular Data and Analysis" portion of this course) to validate the data accuracy, completeness, and freshness of the Ontology.

Datasets that back ontology object types should have two other health checks to monitor the synchronization between the backing dataset and the Ontology storage service:

• Sync Status: A pass/fail check of whether the synchronization between the dataset and the Ontology storage backend.
• Sync Freshness: Compares the date/time of the latest sync with a designated date/time column in the data.

🔨 Task Instructions

Using what you've learned about tabular and Ontology data health, answer the following questions:

• Does the flights dataset back any Ontology object types? (Hint: About )
• When was the last successful sync between the flights dataset and the Ontology service? (Hint: look at the Sync status item in the dataset’s Details tab. The Sync to Phonograph block represents the sync to the Ontology service)
• Does the flights dataset have the Sync freshness and Sync status health checks applied? If so, are the checks passing or failing?
• What is the impact on analysis if either of these checks were to fail?