Hi, (01)
I am not at the same level of expertise on these topics as most of the other
posters on this thread (so calibrate this input accordingly), but I would like
to suggest an additional -- reinforcing -- perspective: Specifically, I think
that a failure to focus, to date, on the value connection between ontologies
and reasoners is _part_ of the problem ... with understanding, engineering, and
tool progress related to ontology development and utilization. (02)
Ontologies are too often seen as definitional or descriptive in nature when, in
fact (IMHO), they are (or should be) operational in nature, where the
operations of interest are the reasoning operations enabled by specific
ontologies or sets of ontologies. Stressing that relationship and value
proposition might tilt ontology developers, consumers, and supporting tool
developers toward a more productive posture...? (03)
Avanti,
BobN (04)
-----Original Message-----
From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
[mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F Sowa
Sent: Tuesday, January 21, 2014 4:04 PM
To: ontology-summit@xxxxxxxxxxxxxxxx
Subject: Re: [ontology-summit] [Bottlenecks] Identifying Bottlenecks in
Ontology Engineering (05)
Dear Matthew and Ali, (06)
I agree with the importance of Matthew's questions. I also agree
with Ali's answers. But I'd like to make different suggestions. (07)
> What is it that takes a lot of time and effort?
>
> Broadly speaking, education and team buy-in. Most people don't
> understand ontologies well... (08)
Yes, but I don't believe that the overwhelming majority of developers
will ever understand ontologies -- either well or poorly. (09)
> What is it that is very expensive?
>
> Access to SME's. The higher the skill and importance of the SME,
> the more difficult it is to get their time.... (010)
I agree. But I believe that we need *radically* different tools.
The SMEs should do their work in *their* preferred languages and
notations. They should *never* be asked to learn anybody else's
notations, conventions, or interfaces. (011)
> What is it that is held up because of a lack of scarce resources?
>
> Generally, ontology development is bottlenecked because of access
> to SME's and access to software developers that need to provide
> adequate infrastructure... (012)
I agree. But the solution is to get the information from the same
sources and tools that the SMEs themselves read, write, and use. (013)
> Formal, computational ontologies in general are not well developed...
> Bindings into alternative reasoning algorithms and evaluation frameworks
> are still quite crude, and require a lot of wheel re-invention... (014)
Those bindings should be made to the tools and resources the SMEs
are already using to do their job. Any necessary ontologies should
*help* the SMEs to do their work better and faster. (015)
> Why is it that ontological approaches are not taken when they
> could/should be?
>
> There are a number of factors. Sometimes, the long pay-off time makes
> these interventions either riskier, or outside the expected pay-off
> for the decision-maker, and hence less attractive... (016)
I agree. But those are symptoms of not having the right tools. (017)
> while the Semantic Web understanding of ontologies is useful for
> certain classes of applications, it is not well suited to many other
> applications... many interventions I've seen don't fully take into
> account the sociological factors of the solution...a broad class
> of potential ontology based applications can be achieved with
> a non-ontological approach faster and cheaper. (018)
More symptoms of inadequate tools. (019)
Fundamental principle: Ontology tools should *reduce* the expense
by enabling SMEs to accomplish more in less time. The ontologies
should be a *by-product* of the SMEs' normal work. (020)
Recommendation: The ontology summit should devote more attention to
cutting-edge research than to incremental improvements on inadequate
tools. Some suggestions: (021)
1. See the slides and publications by the Aristo Project at AI2:
http://www.allenai.org/TemplateGeneric.aspx?contentId=12 (022)
2. The IBM Watson project is also doing research on deriving
knowledge from the same kinds of resources as AI2. (023)
3. Tom Mitchell at Carnegie Mellon developed the Never-Ending Language
Learner (NELL): http://rtw.ml.cmu.edu/rtw/index.php . Or see (024)
http://wamc.org/post/dr-tom-mitchell-carnegie-mellon-university-language-learning-computer (025)
4. For the past few years, I've mentioned Cyc as an important
project that is doing important research with the world's
largest formal ontology. (026)
5. And from time to time, I cite the VivoMind work. For example,
http://www.jfsowa.com/talks/goal7.pdf (027)
I won't claim that these projects will solve all the problems tomorrow.
But I believe that tools based on some combination of these methods will
solve the problems raised by Matthew's questions. They'll get better
results faster than trying to "educate" developers about ontology. (028)
John (029)
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