From Friedrich.Leisch@ci.tuwien.ac.at  Mon Mar  6 11:27:25 2000
From: Friedrich.Leisch@ci.tuwien.ac.at (Friedrich Leisch)
Date: Mon, 6 Mar 2000 12:27:25 +0100 (CET)
Subject: [Rd] Re: [Omega-devel] StatDataML
In-Reply-To: <200003032136.QAA20959@jessie.research.bell-labs.com>
References: <200003032136.QAA20959@jessie.research.bell-labs.com>
Message-ID: <14531.38429.238420.501197@galadriel.ci.tuwien.ac.at>


>>>>> On Fri, 3 Mar 2000 16:36:36 -0500 (EST),
>>>>> David James (DJ) wrote:

DJ> Hi,
DJ> I just had a very quick look at the StatDataML proposal --- nice
DJ> work!   At the risk of showing my ignorance, I want to mention 
DJ> my first impressions.

DJ> My first impression is that defining datasets in terms of
DJ> arrays and list is a bit too high a level.  What about 
DJ> simpler vectors, scalars? (I know that R/S don't have scalars,
DJ> but other systems/applications do.)  Can we think of a core
DJ> set of "basic" data types (factors, strings, integers, etc.)
DJ> from which to build on other, possibly recursive types (perhaps
DJ> similar to corba's IDL basic data types or S's datadump?).

Hmm, basically we have that ... just that I don't see why it's
necessary to differentiate between a vector (=1-dimensional array) and
higher dimensions, i.e., introduce different tags for it. But if many
others feel like this is necessary: I don't have s trong opinion about
it, we just wanted to keep the thing as simple as possible.

Regarding data types: Torsten and I just discussed that we want to
keep the mode of an array as abstract as possible such that
applications can use the internal representation that fits the data
best.

IMO the following modes will be necessary to represent statistical
data:

logical, nominal, ordinal, integer, real, complex



DJ> Would it make sense to imagine, say xlispstat/python/java applications 
DJ> reading  and interpreting an StatDataML document without serious difficulties? 

Sure! What's the difference?


DJ> My gut feeling (which is often wrong) is that the DTD should make
DJ> the data self-describing:  e.g., the factor "machineId" has 
DJ> levels (or defining set) "Stepper1", "Stepper2", ... "Stepper20", 
DJ> eventhough the particular dataset at hand has only a
DJ> subset of those.  Similarly, perhaps allowing  units and classes
DJ> to be included in the dataset (in the case of currency, it is certainly 
DJ> a number, perhaps single precision, perhaps not, with specific units 
DJ> dollars, euros, pesos, etc.)

DJ> More long-term, how about application-defined data?  Application may have
DJ> it's own set of data objects that fully exploits contextual 
DJ> information that could be extremely useful to capture and 
DJ> communicate.

We definitely need (and want) any user to be able to exctend
StatDataML, i.e., define new classes. There should be a set of
standard classes (like dataframe or time series), but also interfaces
for defining new classes.

The current idea (in R) is to have the following: If the SDML object
has a class and there exists a conversion function for that particular
class then use it, otherwise do the default thing.

The conversion function shouldn't do to much, probably mostly renaming
some slots and re-organizing the structure (as claases on different
systems will probably have different structures).



DJ> Also, do the data have to be in ASCII format?  What about 
DJ> (possibly mime-encoded) images? sound?

Hmm, haven't thought about that yet. 


DJ> As I mentioned, these are questions coming from my lack of experience
DJ> with XML, but may be worth raising now better than later :-)

YES!!! That's why we called it ``proposal'' rather than
``StatDataML version 1.0'' :-)

Best,
Fritz

PS: We are also no XML experts!

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[Rd] Re: [Omega-devel] StatDataML
Friedrich Leisch