Re: seeks input on Study Data Exchange Standards An alternative approach

Hi Peter,

Just my two cents: Having read your white paper, I find your separation 
into the "What", i.e. the terminological model (intensional), and the 
"When, Who, Where, Why", i.e. the context/information model 
(extensional), very useful and intuitive.

In your paper, I only found two reasons against expressing both parts of 
the model in RDF or OWL, one being performance and the other limited 
knowledge of clinical modelers. I agree that speed is essential for 
real-time use. Regarding the limited knowledge of clinical modelers, I 
would say that understanding extensional logic is just as hard: As an 
EHR can only express a fraction of reality, its content should not 
necessarily always be interpreted in a closed world (e.g. a patient 
could have a certain allergy even though it has not been recorded). So 
open and closed world reasoning will have to be combined, and it is 
always important to be aware of the consequences. Thus, I think that 
your "Semantic Node Labeling" idea is excellent.

So I don't see any conceptual problem of representing the "When, Who, 
Where, Why" in OWL and making use of reasoners to harvest implicit 
knowledge. In contrary, I just worked with an OWL representation of 
openEHR archetypes [1], and I see many valuable applications for RDF or 
OWL representations of information models. Possibilities are to mediate 
between several standards as in the Salus project [2] or to "leverage 
publicly available data from the Linked Open Drug Data cloud to 
federated querying for type 2 diabetes patients" [3] (Mayo Clinic). They 
exported data of 6.7 million patients to RDF and stored it in Virtuoso. 
I also find the reasoning it enables interesting: integrating rules [4], 
hierarchy / subclass reasoning (i.e. when querying for a "problem" 
archetype, also results from its sub-archetype "diagnosis" should be 
retrieved). Furthermore, validating archetypes themselves as in [5] or 
validating patient data by turning the OWL representation into integrity 
constraints are interesting in my opinion. It could also be worthwhile 
to gain insight into the implicit knowledge contained in patient data, 
to infer relationships between comparable models and to reason on the 
boundary between information models and terminologies. So - in my 
opinion - much work to do!

Best,
Kathrin

[1] http://www.few.vu.nl/~kdr250/prohealth12kr4hc_archetypes_owl.pdf
[2] http://www.salusproject.eu/
[3] http://dl.acm.org/citation.cfm?id=2110415
[4] http://www.ncbi.nlm.nih.gov/pubmed/21118725
[5] http://ceur-ws.org/Vol-674/Paper150.pdf



Op 21-08-12 17:47, Peter.Hendler@kp.org schreef:
> Sorry I didn't make the meeting but just looked at the minutes.
>
> We (Kaiser) do use the Ontology features of SNOMED extensively and 
> have a different take on how it should be done.
>
> Specifically we would not advocate for example, putting FHIR in RDF or 
> OWL.  What we've fount to be simple, useful, and very clean is to 
> recognize the two different kinds of logic involved.
> And keep them isolated to different parts of the model.
>
> Intensional  (like OWL, Open World, Reasoners and inferences)
> Extensional (like HL7 openEHR all Object Oriented models, all databases)
>
> The base of a clinical model is always extensional Object Oriented, 
> but there are nodes (attributes in the classes) that can take the data 
> type Coded Data CD)
>
> For example the "code" of an Observation class takes a code.  You can 
> then designate that the code must be filled with only SNOMED or a 
> SNOMED extension term that follows the same ontological scheme as SNOMED.
>
> If you do this, then you can safely use a reasoner on the "code" for 
> any Observation.
>
> For example you can ask for codes that represent  "a disease with 
> finding site lung structure with morphology fibrosis and disease 
> process autoimmune".
>
> Once you get this list of SNOMED codes then you iterate through them 
> using Extensional logic (SQL) and then you have your list of patients.
>
> This is the clear separation of the intensional and extensional parts 
> of the model.  It is not the representation of the entire model in RDF 
> or OWL.
>
> We are just finishing a second white paper on a suggestion of how to 
> extend this principle.  The basic idea is that clinical models, like 
> HL7 are primarily at the base Extensional OO models and should not be 
> represented as OWL or RDF.
>
> But where it makes sense, you pick particular nodes like the "code" 
> value of the Observation class, and then you add some meta information 
> that indicates the following.
>
> Intensional  TRUE/ FALSE   (the default is FALSE, you can not use a 
> reasoner or SPARQL, this is an extensional OO node)
> If TRUE then you supply the following additional meta tags.
>
> logic  (for example OWL-DL, EL+ "same as SNOMED", RDF etc)
> ontology  (for example SNOMED-CT)
> post_coordinated_experessions_allowed  (TRUE/FALSE)
> hierarchies (for example Clinical Findings, Observables)
>
> Now any user or receiver of a model can scan the nodes for these tags.
> If they find any with intensional="true" then they can inspect the 
> other associated meta tags and know if they can use reasoners or SPARQL.
>
> For the huge numbers of instances of these artifacts (messages or 
> documents) that would be in the millions, you don't want to use 
> reasoners but something faster like SQL. But for the nodes where it 
> makes sense you can use OWL or some other reasoner dependent 
> intensional logic.
>
> In summary, it probably isn't a good idea to just move the model (for 
> example FHIR) completely over to RDF or OWL.  Rather keep it an OO 
> model but then use "Semantic Node Labeling" to designate particular 
> nodes that you are allowed or expected to take advantage of SPARQL or 
> OWL-DL or SNOMED
>
>
>
>
>
>
>
>
>
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-- 
Kathrin Dentler

AI Department         |   Department of Medical Informatics
Faculty of Sciences   |   Academic Medical Center
Vrije Universiteit    |   Universiteit van Amsterdam
k.dentler@vu.nl       |   k.dentler@amc.uva.nl