Hi Nitish, all…
Have you considered approaching it from a semantic modeling perspective, using a GraphDB construct to express it, and expose it for apps consumption as a microservice?
This approach may be particularly valuable for designing and optimizing rapid algorithmic learning loops in the AI / ML / DL space.
The hypothesis here is driving a strong separation of concerns. In so doing. apps consuming this microservice would have the utmost flexibility of addressing NULLs in a manner we may not be aware of yet.
By ‘NULLs’ I mean a temporal service where there may be no value for any of the date attributes – be it a second, minute, hour, date, day, or year. And for a globally-mindful solution, time zone would also play a role in that model.
Further, should there be a confidence level of less than 100% concerning the value of any one or more of the temporal model’s nodes, your Temporal Microservice would provide the capability to expose it as well.
Thoughts?..