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Joshua Allen wrote:
> research project, rather there are large industries (e.g. healthcare
> totals17% of the GNP in the USA) for which such technologies are
Minor nit: USA *blows* 17% of GDP on healthcare every year. Hopefully
XML would make that number *smaller* :-)
No minor nit indeed -- that is tax $$ out of your and my pockets. Having
studied this problem in some depth for several years I've become convinced
that "semantic web" _like_ technologies are the only viable solution --
essentially the data needs to be majorly cleaned up to allow automated
processing. Converting the data to XML is just the first step, the next step
is that the data needs to be better classified which is where "semantic web"
technologies i.e. ontologies fit into the picture. My view of "ontologies"
is that they are a way to take what looks like free wheeling data and give
it a _very precise_ (and hence machine processable) definition. Since the
medical terminology size easily exceedes 200,000 terms (by SNOMED alone, and
there are a number of other important healthcare terminologies) other ways
of defining controlled terminologies aren't appropriate to the task -- can
you imagine what a complex XML Schema that defined >200,000 elements and
types would look like? In my view, XML is indeed part of the solution, but
doesn't itself answer the question of what we do with all that data once it
is in XML.