Thanks for the reply, Micha.
I know the procedures you showed me, but once you have identified the values that have not passed the tests, in a project that contains 4000 angular measurements divided into 100 campaigns (Groups), analyzing the stationing in which the anomalous value resides, is not difficult but rather slow, because you have to scroll one by one or in groups to find the stationing with values out of tolerance.
We have organized the work in Jag3d by measurement campaigns and therefore by groups, each campaign is named with a sequential number, the date, and obviously the station to be oriented.
What do I do with it then?
Nothing particular, once I have the value out of tolerance and the corresponding campaign (group) I go to recheck the data I have loaded and check the anomalous angular values with respect to the history that I have available on other software and I make my decisions about it.
I believe it is an implementation that would greatly facilitate the analysis and "debugging" of the uploaded data.
If you think it is appropriate I can send you a sample project.