i'm trying to use the recently advertised DMN (DMN Decision requirements diagram, DMN Decision table model, DMN Invocation model) but I really miss any (!!!) description by Software AG of how to realize it like the OMG intends it to.
Does anyone already done it?
Is anyone out there having an example for me having realized the described DMN example (--> attached, page 145) in ARIS?
very happy to see your interest in modeling DMN with ARIS. We are still working on enriching the DMN capabilites, however, I want to provide some examples, which hopefully clarify your questions.
First of all a DMN Decision Requirement Diagram (DRD), which is quite similar what is shown on page 147 in the spec.
For that, you have several specific objects/symbols...
... and of course connections:
To make decisions based on the just mentioned requirements, you use the DMN Decision Table:
Moreover, you are able to define a context related to a decision with the DMN Context Diagram including e.g. the following objects:
as it seems in the decission table rows and colums are switched (i.e. rules are defined in columns and not as usual in rows). Is it possible to switch rows and columns to get the standard-design?
And: To what conformance level do the exports of ARIS-DMN reach? I mean: Is it possible to prepare a complete DMN-XML with ARIS to deploy and run?
What is the difference between the DMN Decision table and the DMN Decision Table Model.
A little background to the question. I built a PFD and on one of the L4/L5 ACT/TASK objects have added an assignment to a ''DMN Decision Requirements Diagram & DMN Context Diagram''. So the decision routing is from the Task (OBJ) to the Decision (OBJ). The decision object allows you to add 1x DMN Table and 1x Decision Table Model. However I am unsure of what the difference is between the two and does this mean we can only have one of each table against any 1 Decision object (assigned to)
Any guidance is much appreciated.
Example attached. The first is the DMN Decision table and the second the DMN Decision Table Model (All data is completely fictional)
