RE: [huml-comment] RE: Apartment Clerk Informal Scenario

["Bullard, Claude L (Len)" <clbullar@ingr.com>]

From: Dennis E. Hamilton [mailto:dennis.hamilton@acm.org]

>My first thoughts are to layer things, as you put out.

>1.  Take this example (even though it seems far-fetched in the present) into
>a future "likely story."  Assume that there is some sort of appliance (maybe
>even an ear piece) used by the clerk.  Simplify the idea of the technology
>and consider that an electronic advisor is actually used.

One reason to annotate information is so that it can be reused in multiple 
contexts including machines and systems which we have yet to create or 
envision.   It is precisely this lifecycle aspect that is the prime reason 
to use markup.   It is the notation that can determine such.  For example, 
an electronic advisor given an ear piece might be using VoiceXML or even 
MPEG files.  But the metadata that enables a selector to choose the right 
file to present would be HumanML.

>2.  Look at the layers between this likely-story situation and the nature of
>the application and where the database or knowledge base that is drawn on
>comes into it.

HumanML-derived languages are likely in this scenario to be annotation languages.  
They describe the instance at hand in terms of that metadata.   Consider the 
woodland troll.   We know it is a troll; what do we need to know to figure 
out it is a woodland troll, first, then what information is stored that 
is generic to all woodland trolls as opposed to say, mountain trolls.  Such 
information may include artifacts of dress, habits or gestural types, different 
haptic values used for intimate vs business communication, and so on.  If a 
woodland troll meets a mountain troll and wants to woo her, it can be awfully 
useful to find out about food allergies of mountain trolls, family relationships 
(eg, are mountain trolls paternal or maternal:  figure out which sex inherits 
wealth and which parent to ask for her green hand in marriage).

>3.  Look for what is essential about HML being used down there, and how is
>it used and by whom.

HumanML in the primary schema, is just a set of categories of information 
types that influence human communication.  We can apply these to humans 
directly, and by analogy, to trolls.   So it is just metadata.   How and 
who uses it can vary greatly.   But let's say anthropologists keep a 
database on trolls the same way the US CIA keeps online factbases about current 
nations.   If the data has HumanML annotations, a program could conceivably 
do such things as create a prototypical troll, then a woodland troll, or 
even a woodland troll from Hyborgea in the 8th Age of Zork without having 
to do all that research for themselves simply by querying the public database.  

I'm making this up, but the point is, the HumanML categories provide contexts for 
specializing the human.  Again, it works as well as the category values 
collected are correct.   The HumanML categories themselves, what is in 
the primary, are a "theory".   We are pounding on them to see if we have 
consensus that the "theory" itself is what is needed.   They should accord 
well with semiotics theories in the broad sense.

Let's take another example.  I am a marketeer for an European company that wants to create 
a market campaign for the American South.  Where can I go to get information 
that will help me select the right texts, images, dress styles, and even 
current event controversies that will provide a positive image in terms 
of the target market's culture?  Further, can I tune that even more specifically 
to a smaller region?  Can I avoid stereotypes when I do this?  Can I usefully 
apply stereotypes without being offensive?  Tricky stuff, but having annotated 
samples can help one choose.  Consider the problem of the western observer 
and the Indian males who hold hands.  Is that a gesture I want to use in Bombay, or 
is it only a habit of say, smaller villages but not practiced in the larger 
cities, or does is vary between northern and southern india?   A HumanML 
database that has geotemporal attributes helps.   Think of all of the movies 
you've seen where an alien lands on our planet dressed in clothing and speaking 
in the styles of the 1950s because their sources, TV broadcasts, have the 
speed of light time delays.   If you go to Nebraska, a Canadian looney is not 
legal tender, but if you are in say, Maine, a vendor may accept it because 
you are close to the boundary.  (Boundary conditions are especially interesting.)

>That is, we are navigating some layers of abstraction to get to how HML at
>(3) [what is in some sense the likely direct use, as a plausible story] is
>"worked" to contribute to the situation at (1) and exactly what is the gain.

>One key question I then have is what is the point and purpose and value of
>interoperability at that level?

It is as valuable as the theory is descriptive of what is actually observed, 
in other words, ontologies are theories about things.  One commits to the ontology 
(agrees to its semantics) and applies these.  If it proves to be too expensive, 
too fuzzy, or just plain wrong, it's time to get a new theory.   But without
HumanML, as currently conceived, we do not have a stake in the ground, a hypothesis 
to test.   This is true of XML Schemas in general.   They are theories about 
documents.

len