Sure, Amanda, and that’s why I (and we) advocate using natural language vocabularies that are linked/mapped to ontologies. This was a hard lesson learned (initially,
by others, before my time) in the DoD in the early 1990s, and that I personally experienced in the metadata wars of the 2000s, where people will fight to the death to include their “words”, mistaking these for the concepts behind them.* The important point
is that if you shoehorn peoples’ semantics into “common” vocabularies or ontologies (and it’s worse for the latter, because then you obliterate their differentiating semantics, not just how they refer to things), they may say they will agree with that concensus,
but they will drag their feet, and the “information-sharing” effort will fail.
*This also means that you need to differentiate between stakeholder committees and dedicated small ontology teams, where the latter work in the background to
define the semantics they hear the committee members (often domain experts) describe in the foreground.
Thanks,
Leo
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx]
On Behalf Of Amanda Vizedom
Sent: Thursday, November 22, 2012 1:23 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] doing standards [was - Re: Webby objects]
<climbs atop a small pile of soapboxes>
(1) Controlling language -- setting and using naming standards, for example, -- is *much* harder than building and using shared ontologies. Why? Because language and naming are things humans do/use constantly, are part of their natural
behavior, are intertwined with cognitive and behavioral adaptations in many ways. And standardizing the language people use away from their ever-adapting expert language interferes with that adaptation. If the job needs to be done, the tension here is (correctly)
going to resolve in favor of the adaptation and away from the standardization.
(2) It is a central, advantageous feature of ontological representation that it can enable and support shared models, shared metadata, and interoperability *without* requiring controlled and standardized language use. Not all ontology-based
projects have staff with sufficient training to understand and use that advantage. Those that don't use it end up bogged down in naming and language debates.
(3) Available out-of-the-box tools (and standard KR languages) need to grow to support and emphasize this feature and ontologies (for example, via built-in support for specifying multiple labels for a concept, with lexical and localization
information for those labels, and support for viewing/browsing an ontology with some specific localization used to select display labels. This is pretty easy compared to many other ontology-interaction problems. But it isn't there in the off-the-shelf stuff
(in contrast, it *is* there in a range of commercial/proprietary and/or in-house tools that have to deal with multilingual, business vertical, or other localizations.
(4) One reason people don't use ontologies more is because there is no consensus on quality and methodology, and they don't know who to trust. Those who say the have the One Methodology To Rule Them All are at best no better than everyone
else at delivering something useful. That's because we *don't* need One Methodology To Rule Them All. We need a good understanding of what ontology features matter to what kinds of projects: that is, an understanding of what it means for an ontology to be
suitable for an application, fit for a particular use case.
(5) Until we build that kind of understanding -- at least a start -- some people who could benefit from ontology applications will continue to balk at the lack of clarity, while other people will go ahead but invest in ontology that is
mismatched to the requirements. The latter experiences make the climate for ontology adoption worse.
(6) I suggest that it should be very high on our priority list to work on building that shared understanding of the relationships between use case features and suitable ontology features. We can really only do that effectively as a community,
sharing experiences and collaborating on the lessons learned. There are enough of us, across industries and sectors, to get going and make progress on this. There are also many who won't share just yet because they aren't sure whether the payoff of sharing
outweighs their trained resistance to making in-house knowledge public. We can still move, and try to pick them up as we gain momentum.
(7) A good ontologist can, in fact, come in and build something and make a difference in two weeks. BUT this assumes that it is clear what the ontology is for, how it will be used, what requirements come from downstream, and what sources
are to be regarded as authoritative, AND that the ontologists is provided access to those sources. The reality is that the ontologist often walks into a situation in which few or none of those conditions are met. Sometimes it just hasn't occurred to anyone
to do them; sometimes it has but no one knows how. Sometimes an experienced ontologist is actually there who knows how, but isn't give the authority or resource access to do this requirements identification. Result: value not delivered. I suggest that (6)
is also important because it begins to address this problem by building shared understanding of what use case features are important to identify.
</climbs down from soapboxes to go check on roasting turkey>
On Thu, Nov 22, 2012 at 12:17 PM, David Eddy <deddy@xxxxxxxxxxxxx> wrote:
Peter -
On Nov 22, 2012, at 10:24 AM, Peter Yim wrote:
The basic question is "Why aren't practitioners using
ontologies?"
Because they're really, really, really HARD, aside from the fact that management has no idea what all the handwaving is about much less what any potential value might be.
Plus the little detail of there being no foundation. So ontologies are very much ivory towers in the clouds, particularly in commercial IT. Science/bio/pharma may very well be a different story since Mother nature has been carving the
hierarchy for a few million years. In commercial systems the concept of ordered hierarchies & languages is at best a distant fantasy.
It has been my direct, commercial experience with Fortune 500 organizations that very few (approaching none) have anything approaching something simple as "naming standards" (conventions—3 ring binders on the shelf, yes. Enforced no.).
Obviously some systems have naming conventions, but that was typically driven by a single motivated individual & is not carried over to the next systems(s).
Please to acknowledge the scale here... a Fortune 500 scale organization will have something like 1,000 to 5,000+ IBM mainframe applications. This is not counting client/server, web, *nix, iSeries, etc. Pretty much every one of those
applications will have uniquely opaque language.
I would argue that if the organization does not have the discipline to control its language something as pie-in-the-sky as ontologies is a castle in the sand.
The reasoning/experience is that if they're as big & important as they are without naming standards, why bother.
It is my assumption the same thinking & non-action carries over to the much more complex ontology domain.
If the ontology consultant (that's singular) could show up on Monday & create something substantive in a week or two, AND get easy-to-use & understand results into the hands of the grunts, things would likely be different. Requiring the
grunts—the data entry/programmer/analyst folks doing the work—to learn yet another collection of technical languages is not a route to adoption.
Does anything in the ontology domain deliver something that's as easy-to-use & mindlessly useful as a spellchecker? Protege may be a wonderful product, but it's not even remotely close to being an end-user tool.
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