Re: HL7 RIM Designtime OWL Runtime RDF

Hi Siviram,

On Wed, 2013-01-16 at 14:51 -0600, Sivaram Arabandi, MD wrote:
> I am enjoying reading and catching up on this thread. 
> 
> David, you mentioned 'rdf model' below - are you referring to ontology
> models? 

Yes, sort of.  One can design an RDF model without formalizing it into a
written ontology.   So I was referring to the schema of the RDF data --
classes, relationships, etc -- whether or not that schema is implicit or
explicit (i.e., written into an ontology).

> And, you said "To my mind, monotonicity is the key."  But in medicine
> most reasoning is non-monotonic  - default reasoning, (educated)
> guesses and revision of diagnosis as new data comes into the picture.
> What am I missing here?

Today you might conclude "As of 16-Jan-2013 the diagnosis is X", but
tomorrow you might conclude "As of 17-Jan-2013 the diagnosis is Y".  If
you represent the statements that way (qualified by the particular
context or, in this case, date) then they are monotonic -- they remain
true forever, regardless of what new information arrives.  Whereas if
today you were to represent that information simply as "The diagnosis is
X" then it would be non-monotonic, because tomorrow you might need to
change it to "The diagnosis is Y".

OTOH, even if the data is monotonic, you can cleanly use default
reasoning and the closed world assumption in the way you *use* that
data.  For example, if the data is represented like "As of 16-Jan-2013
the diagnosis is X", then a query can return the *latest* diagnosis and
report that "the current diagnosis is X".  Tomorrow, after more data has
been added, that same query might report that "the current diagnosis is
Y".

You can think of "the current diagnosis is X" as being derived,
non-monotonic data.  If you store it, you must be careful to treat it
only as cached information that will be invalidated when its antecedent
information changes.  The RDF Pipeline framework that I've been working
on
http://code.google.com/p/rdf-pipeline/
was designed in part to handle this kind of problem: to keep track of
information dependencies and update derived non-monotonic information
automatically.  Here are slides about it from last year's Semantic
Technology conference:
http://dbooth.org/2011/pipeline/

You can also design your RDF data models so that certain pieces make
closed world assumption or use defaulting conventions.  Then you have to
be careful to keep track of which pieces they are, so that when you
merge data you do so appropriately without invalidating anything.  For
example, you might change defaults into explicit values before merging.


-- 
David Booth, Ph.D.
http://dbooth.org/

Loss of web prodigy Aaron Swartz: http://tinyurl.com/ahe2k8c

Opinions expressed herein are those of the author and do not necessarily
reflect those of his employer.

Received on Thursday, 17 January 2013 02:14:25 UTC