Re: An argument for bridging information models and ontologies at the syntactic level

Hi Chimezie,

It may be helpful to examine what "data" means and what "measurement" means.

There is a kind of classification system that is used in medicine.

The "process of living" includes many hundreds of thousands of 
sub-processes that must work in harmony for the individual to remain alive.
These sub-processes each have a "status" at a given point in time.
We can perform measurements that give us data about the status of the 
sub-processes. However, the data is meaningless without interpretation:
Are the values we receive from measurement free of error? Most tests 
will guarantee that the data is only 95% free of significant error.
If the value can be assumed to be free of error, does the value 
represent a significant change in the state underlying process being 
measured?
If the state of the underlying process is significantly changed, does 
the change represent "dis-ease" or does the change just represent a 
"variant of normal," i.e. a temporary normal abberation in a processes?
Note that there is not always agreement about when a variance of normal 
process function actually constitutes a disease or "diseased process." 
Of course, life is only compatible with relatively minor abnormalities 
in body processes. Major abnormalities lead to immediate death.

So we are left with some important concepts that need to be fit into an 
ontology that is useful to scientists and clinicians.

"Living is a set of processes; disease is a slightly abnormal process in 
the midst of many normal processes. We only know about these slightly 
abnormal processes by making measurements of some sort that proxy for 
the "state of the process." Usually, one kind of measurement is not 
sufficient to tell us much about the status of a processes. From a 
series of different kinds of measurements, one can make conclusions 
about whether the state of the process is permanently abnormal or just 
transiently abnormal. One can make conclusions about whether the process 
is becoming more abnormal or becoming more normal."

Now with this perspective, perhaps you can better describe how a disease 
is different than data?

Dan


Ogbuji, Chimezie wrote:

>A (perhaps) naive question, inline below.
>
>  
>
>>-----Original Message-----
>>From: Dan Russler [mailto:dan.russler@oracle.com] 
>>Hi Dirk,
>>Your understanding of "disease" is entirely in synch with mine.
>>However, my professors in science felt that all measurements 
>>were abstractions with a high degree of potential error, 
>>including medical signs.
>>
>>So the basic issue is that "disease" and "medical sign" are 
>>more similar than different in most properties, 
>>e.g.significant introduction of judgement in the measurement 
>>process, their propensity for error, the need for 
>>re-evaluation at a later date, etc.
>>
>>Level of abstraction is simply a gray scale and cannot be 
>>classified into "sharp borders" that can be independently 
>>validated by multple classifiers. Therefore, there is no 
>>distinct classifcation between "medical signs" and "disease."
>>    
>>
>
>The distinction that I've been using is that medical signs are
>measurements (as Dirk says), and thus 'data' (in the sense that they
>live in some communication media - digital or paper depending on the
>medical record system).  Diseases are 'pathological dispositions'.  This
>is very much a BFO-ism (for lack of a better word), but it basically
>means that they are the potential to manifest a process (a pathological
>process) that can (often) results in a pathological formation.
>
>I'd be curious to hear if this philosophical distinction matches the
>underlying science here.
>
>Chimezie (chee-meh) Ogbuji
>Lead Systems Analyst
>Thoracic and Cardiovascular Surgery
>Cleveland Clinic Foundation
>9500 Euclid Avenue/ W26
>Cleveland, Ohio 44195
>Office: (216)444-8593
>ogbujic@ccf.org 
>
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