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RE: [xml-dev] XML Design for Diverse Data

Even for compound documents, extension by the NVDL method seems even
scarier than the ANY element - at least you know where ANY is going to
show up.  

In the context of developing a schema for the exchange of trademark
registration data among WIPO and states party to the Madrid Agreement,
OHIM put ANY in the base schema with the intention that it be replaced
by those additional elements required by each national office for their
internal processing not already provided for in the base set.  Other
offices would, in general, ignore those easily-identified elements.  As
elegant as NVDL appears to be, the unpredictability it introduces is not
just in machine processing, but in business processing as well.
Industrial property offices don't usually want to see data in a
submission that is not supported by some business rule.  Extraneous data
can create considerable confusion and potential liabilities.  Somewhere,
somehow, the overall business process has to be controlled in order to
reduce it to machine-based processing, that it, it has to be minimally
predictable, or the business won't invest in automating it.  It's fairly
easy to show customers how an XML schema makes their business objects
amenable to machine processing.  I don't think I'll be introducing NVDL
to them any time soon.

We currently publish 10,000 patent documents each week based on a DTD
with an external table DTD and MathML and expect to introduce some
others.  So far, we haven't needed NVDL.

Bruce B Cox
Manager, Standards Development Division

-----Original Message-----
From: bryan rasmussen [mailto:rasmussen.bryan@gmail.com] 
Sent: Wednesday, April 23, 2008 11:57 AM
To: George Cristian Bina
Cc: Costello, Roger L.; xml-dev@lists.xml.org
Subject: Re: [xml-dev] XML Design for Diverse Data

> NVDL is the solution once you have the problem of validating
> compound documents.
I agree when I think of compound documents as XHTML with MATHML and
SVG and RDF mixed, I find it problematic when thinking of exchanging
business data.

Bryan Rasmussen

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