Thanks John. (01)
I agree, ontologies are not in the same category as any of these
tools, but the conversation I'm proposing would be with developers
directly, not SME's or CIO's unless the CIO is the main developer),
and so requires a 2-step process. It's not about promoting specific
ontologies, or even ontologies in general. It's about promoting the
tools to use with ontologies first, and for this audience specifically
promoting Cyc or SUMO is what creates the blank stares in the first
place. (02)
Not all successful open source projects are on the scale of the ones
you listed, and not all are as fundamental as an OS or a programming
language. They do however piggyback of their success and adoption.
Ease of development is what the Ruby on Rails framework provides. It's
very popular only because it allows developers to build and maintain
an application quickly. There's is nothing revolutionary about the
Model-View-Controller (MVC) paradigm that Rails implements, but it is
the convention-over-configuration principle that people find so
natural. And all this became possible because of the natural and easy
syntax of the Ruby programming language in addition to MVC. (03)
If we talk to the developers who know their own systems
inside-and-out, and allow them to incorporate ontologies via tools,
they will go to the CIO's and CEO's for us and show them how much
better the existing system is with ontologies. I see this in the tech
startup community all the time with other new technologies and
paradigms. (04)
To promote ontologies directly, perhaps promoting partial ontologies
for specific purposes would be more helpful. Or even extracting axioms
out of upper ontologies that deal with a specific topics and addresses
a company's main problem. This is no easy task, but necessary if we
want to get some traction. (05)
By no means ontologies, simpler representations of semantics like ones
in RDF get the ball rolling and provide a starting point for the
conversation. The topic of linked data steers people in the wrong
direction, and gives illusions of pie-in-the-sky solution that won't
create profit right away, if ever (I'm hopeful). (06)
As an example, developers understand the benefits of data-mining in so
far as they can get a tool that quickly plugs into their existing data
and starts showing results they are familiar with, only better. What
developers that work with data understand is the power of statistical
analysis like identifying patterns in data. Data-mining is a more
complex and powerful way of going past a query like "average age of
user" to "average habits of user with X properties". Replacing SQL
queries for "X properties" with semantically driven inference is
something they do understand. Unfortunately there is no tool for them
to do that quickly and see the benefits for themselves. (07)
On 4 March 2011 12:34, John F. Sowa <sowa@xxxxxxxxxxx> wrote:
> On 3/4/2011 11:03 AM, Bart Gajderowicz wrote:
>> If we look at the way Open Source applications become popular, we see
>> it's the ones that are adopted by developers. When this happens, the
>> developers become the salespeople on mass. They then propose the
>> solutions at the grassroots level, directly to the customer.
>
> The most successful open source projects have a clear, well-defined
> goal with a binary metric for success: it works or it doesn't.
>
> There are three kinds of examples:
>
> 1. Implementing a clearly defined specification: Linux and BSD.
>
> 2. Extending and continuing a system that was started by
> a commercial company: Mozilla, OpenOffice, and Eclipse.
>
> 3. Extending and continuing a project that one innovative person
> developed to a useful stage of completion: Perl, Python, PHP.
>
> Ontologies don't fit any of these categories. Somebody can give
> you a complete ontology like Cyc or SUMO, and there is still a huge
> amount of work to develop a useful application. A partial ontology
> is even less likely to be useful.
>
> John
>
>
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--
Bart Gajderowicz, MSc.
Ryerson University
http://www.scs.ryerson.ca/~bgajdero (09)
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