Hi, I know that this is probably something very inappropriate but I happened to need such a solution. An example:
CLUSTER [AAAA] CLUSTER [BBBB] Some type of finding (a lesion: ulcers) ELEMENT [CCCC] A Feature of the finding (i.e. bleeding) v: some value ELEMENT [DDDD] Another Feature of the finding (area) v: some value ELEMENT [DDDD] Another type of finding (a lesion: atrophy) v: some value OR null_flavor My problem is I want to be able to state whether CLUSTER[BBBB] is observed (True) or not (False) when both features (ELEMENTs CCCC and DDDD) are not present (NULL). I am perfectly able to state it when the data structure is an ELEMENT. Problem arises when none of the features (attributes) of CLUSTER [BBBB] is observed and that two things can happen: 1) None of the features could really not be assessed, but there is definitely an ulcer (presence=TRUE) 2) The lesion in CLUSTER [BBBB] is not visualized at all (Presence=FALSE). But then we need to know why (classical flavors of null)? Of course a straightforward solution is putting under each CLUSTER with child nodes, a new ELEMENT describing its "presence" with Boolean type and with null_flavor. However if it will not break very badly current semantics and other strategies, the advantages of such approach might be: 1) Reducing size, manageability and understandability of (big) archetypes 2) During querying of leaf-nodes in a huge repository, the search algorithm can first check parent nodes' presence and then further go down to leaf-nodes. If a whole branch is not valid/null from the top, then there is no need to look for lower levels and the performance might be enhanced. I might be making a horrible proposal here technically or even there exists another solution already, but this is what I need. Best regards, Koray Atala, M.D. _______________________________________________ openEHR-technical mailing list openEHR-technical at openehr.org http://www.chime.ucl.ac.uk/mailman/listinfo/openehr-technical