Re: Arcs

Hi Murray,

On 21 Oct 2010, at 12:24 PM, Murray Altheim wrote:

> On 21/10/10 23:54, Andrew S. Townley wrote:
>> On 21 Oct 2010, at 11:31 AM, Patrick Durusau wrote:
>>> On Thu, 2010-10-21 at 15:36 +1300, Murray Altheim wrote:
> [...]
>>> It is a question of semantic software recognizing owners' flags rather
>>> than training owners to use different flags.
>> 
>> isn't the above what we've been trying to do for the last 30 years? :(
> 
> Hi Andrew,
> 
> Not really. As a species we've been trying to communicate with each
> other since we could grunt, and none of the issues inherent in that
> communication have gone away. What has changed is the availability
> of tools that permit at the very least the complete availability of
> documentation of what it is we're attempting to communicate, i.e.,
> the ability to fully spell out (literally) the definitions of our
> terms and relations in ways that permit discovery and analysis, to
> both human and machine. These systems are still by and large horribly
> primitive, but they exist for the first time. We can largely credit
> Roy Fielding for this.

I'd agree with the hat tip to Roy for sure.  I guess I wasn't very clear in my own semantics, but I was actually referring to all of the AI work and natural language processing (*that* NLP) inference work that's been going on during that time.

It's an immensely complex problem, so solving it will take some time for sure.  I just see that there's two main camps for trying to address the "getting software to recognize owner flags" part: the machine-centric and the human-centric approach.

The machine-centric approach is what I mentioned above, based on formal semantics and including people like Sowa and the whole ontolog community (broad generalization alert!) as well as many of the DARPA dollars you mentioned.  This approach very much is focused on trying to encode semantic discovery into systems so that they can interpret these owner flags however said owners would like to state them.  All the better if they're in a controlled vocabulary like RDF+OWL of some variety, but hey, that's OK, right? ;)

(BTW, I don't have anything against John Sowa, and I have a lot of respect for his work.)

The human-centric approach to me is much more exemplified by Topic Maps and was one of the main personal draws when I stumbled into this space in 05/06 even though I'd been walking in that direction without realizing it for several years before.  However, Topic Maps also seems to take much more of a "train the humans" to express things in ways that are more easily processed by a system.  PSIs are a very obvious example of this in action.  Whether it strikes a good enough middle-ground is obviously a bigger discussion, but I think it does several things better than some of the alternatives.

> 
>> Funny how semantic software that was supposed to eliminate
>> interoperability problems has caused a new batch of interoperability
>> problems. Some of it is a direct example of Murry's "flag planting"
>> but some is that there's always a domain boundary people hit or
>> adaptations that need to be made to make applications efficient
>> in a particular context.
> 
> I think that most of these problems are simply poor design. There's
> no way to legislate good design, nor keep software designers from
> jumping into solutions before they understand the actual problems,
> nor from jumping ignorantly or fully cognizant of the rules they're
> ignoring.

I'm not sure I agree with you about "most", but certainly a good few.  I've a few pet peeves about "good design" that I won't bring into this discussion, but I think that as it becomes easier to create  functionally useful software where design is in many cases optional as long as it works, this problem isn't going to go away, and we're standing on the beach saying "go away" to the oncoming Tsunami.

Real innovation always happens on context boundaries, and, let's face it, you're going to get it wrong more often than you get it right.  The other thing is that there's 10M opinions, most of which are commentary on probably 10 core principles.  The trick is to express those principles as clearly, concisely and accessibly as possible so those wanting to avoid some dead ends have obvious places to look.  *then* they can choose to ignore the rules if they (think they) fully understand them and the implications of so doing.

> 
>>> Solutions that rely on adapting people to software are deeply
>>> problematic.
>> 
>> Hard enough getting people adapting to people correctly! :)
> 
> All we can do is work on a principle of agreement: if one uses this
> term and we provide you the documentation and one has read the
> documentation and one understands it in the same way as we understand
> it, then we are communicating. Ugh. Difficult, yes.
> 
>> However, that's exactly what we're talking about here.  There's got
>> to be some level of broad agreement on how you bridge the semantic
>> silos so that these identifiers are truly interoperable--and these
>> are as much people issues as they are technology issues.  Some great
>> work has been done in this space, but I'm not convinced it's widely
>> enough publicized so that people on the ground are aware of it
>> --especially those of us who came to the party relatively late.
> 
> This is asking the wrong question. You can't bridge those silos
> without doing damage, if by "silo"  you mean a domain of knowledge
> developed within a community for a particular purpose, being used
> outside of that domain by a different community with different
> understanding. I *completely* agree that this is not a technological
> issue, but technology can assist in providing the solution by at
> least providing the ability to discover and analyse the documentation
> of the terms and relations used.

I didn't realize I'd asked a question... ;)

> 
> To my knowledge, nobody has gone down this path, but technology can
> also provide for *dialogue* in dynamically negotiating agreement.
> Normally it's just the fudge factor (I have never seen a duck nor do
> I know what a duck is, but I've read the documentation and I think
> it sounds like a duck, walks like a duck; must be a duck).

Actually, I wasn't speaking of domain knowledge silos in this case, rather of representation technologies and the bodies of knowledge (and underlying assumptions) that go with them.  Is what you say is the "same" really the same as what I mean when I say "same" because of the perspectives used to determine sameness.

This is also the crux to me of the difference between the machine-centric and the human-centric "schools of thought" I mentioned above, and it depends ultimately on how much utility a human can get by applying the "fudge factor" you mention.  In fact, aspects of my implementation try and codify specifics about the "fudge factor" applied in making these determinations.  Potentially, it could be useful for the types of negotations you describe.

> 
>> I totally agree that more emphasis in this area would be very useful!
> 
> One of the more interesting areas of research in AI/KR is context,
> with at one point yearly conferences solely focused on the subject
> (e.g., [1]). Topic Maps have a rather primitive concept of context
> in the use of 'scope' that could be expanded, possibly within the
> existing model, or perhaps we need to elaborate.  We should be
> paying more attention to the results of that research. I seem to
> remember David Kirch and Patrick Brezillion as central figures,
> people to check out.

I wasn't aware of those names, but thanks for mentioning them.  I also wasn't aware of the conference, but the whole area of context and how to represent it sufficiently to be useful - in another context, of course - has gotten a lot of thought cycles from me over the last several years.  I certainly agree that the scope stuff is, while useful in limited cases, one of the weaker areas I see in the whole Topic Maps space.

Information is data in context, and without adequate ways to represent and convey that context, you're open to lots and lots of issues.  Obviously, all of us deal with this problem every day in many different aspects of our lives.

You said "at one point" above.  Are you aware of particular ongoing efforts beyond the names you mention?

> I also think it behooves everyone to do a bit of epistemological
> homework before jumping head-deep into the pool of modeling. It's
> a deep pool and the bottom is littered with the bodies of those
> who have gone before us and had no ability to swim. I won't name
> names, but as a hint they had lots of DARPA money.


I'd strongly agree with this as well, however, you're going to have to deal with the collision of "those who know how we know" with "those who know X" and there's a lot more of the latter than there are of the former.  Gets back to the points earlier that you and Patrick raised, but the perfect model is useless if it isn't usable in the wild by real people on a daily basis.  I know you know this, but that's one of the biggest challenges I see in this whole space.  We need stuff for the masses that helps meet the epistemological criteria, and I think we're still a long way from many examples of that kind of system.

Cheers,

ast
--
Andrew S. Townley <[email protected]>
http://atownley.org