Cognite Data Fusion: Data Set Archive Feature That Also Archives Data Within the Data Set

Hello!

After reading the documentation for CDF Data Sets I ran a few experiments with the Python SDK, creating assets, time series, and data points all within a data set.  When I was done, so as not to clutter up the CDF instance we are all sharing while prototyping, I selected my data set within the “Create, view, and manage data sets” and clicked the “Archive” option.

I browsed back over to the Assets page, but was surprised to still see my assets from my archived data set visible within the CDF UI.  I thought maybe it was just because of eventual consistency as we all struggle with that with distributed systems.  After a while I check the documentation and saw this:

Edit and explore data sets | Cognite documentation

You can also edit the data sets to add more documentation to them, or to write-protect them to provide an extra layer of protection to production-critical data. By archiving data sets, you can hide data sets that are no longer used.

 

1. • Archive data sets to hide them from the UI and make the data set unavailable to users. The data set and the data it contains is not deleted, and you can always restore archived data sets later.

It seems to describe "write-protect" as something that affects the data, preventing others from inserting, updating, or deleting rows within that dataset. Then when Archive is described it says, "hide data sets that are no longer used" and "make data set unavailable to users", where I believe the natural assumption for the reader would be that data set is a set of data and operations on the data set affect the set of data in that data set.

I understand that how the feature currently works is desired behavior, as Torgrim Aas had explained to me, “Datasets must be considered more like "labels with metadata" since it does not affect the data within the dataset. It only allow users to extract group related information about the data, which can span across different data sources.”

But could we also add another option to “Archive Data Set, Including Data”?