Leo, Hans, and Rich, (01)
We all agree that common semantics is a prerequisite for any kind of
communication among people and/or computers. I would also add that
we need some common semantics even when we communicate with our
beastly friends and foes. (02)
Questions for this forum: How much common semantics is required?
How should it be encoded? Is it primarily task-oriented semantics
that changes from one transaction to another? Should it be encoded in
a large shared general ontology? In some collection of task-oriented
modules or microtheories? In some implicit or procedural knowledge
encoded in procedures (for computers) or in habits (for people and
other animals)? In some mixture of formal logic, informal natural
languages, procedures, habits, or miscellaneous? (03)
And the thorniest question of all: How do we accommodate the trillions
of dollars of legacy software in daily use for mission-critical systems
that won't be replaced for decades to come? (04)
JFS
> But you can get a great deal of successful
> interoperability without assuming a fully axiomatized formal ontology. (05)
Leo
> Sure, by a human programmer hard-coding the interoperability. My point is
> that we all share an implicit ontology, and implicit semantics, to achieve
> something like 95% commonality. As computer scientists, of course, we also
> want to achieve explicit machine-interpretable ontologies. (06)
I think we agree. But that little word 'also' hides the questions
mentioned above. (07)
HP
> ... we tend not to ask too many questions lest we find the answers
> unpleasant or discomforting (and not just to ourselves) (08)
I very strongly agree. We have been talking about ontologies for years,
but we haven't come to grips with the fundamental questions that make
all the great theory irrelevant to mainstream IT. I summarized some
questions above. For other questions, see the end of this note. (09)
RC
> The variation in belief systems among people is incredibly large,
> much larger than can be appreciated by most STEM professionals,
> who are so focused on our own questions, tasks and other daily
> minutiae we don’t even get exposed to widespread views. (010)
I agree, but I would also cite other issues we must consider: (011)
1. People have been interoperating with other people from time
immemorial, even though they have major disagreements about all
the issues Hans and Rich noted. (012)
2. Computer systems have been interoperating successfully since the
1960s without any formal ontology. Many versions of structured
programming, analysis, design, etc., have been useful and some
of the methodologies use logic in ways that have a high overlap
with ontology (cf. the ANSI/SPARC conceptual schema from 1978).
But 99.9% of all the specifications are still written in NLs. (013)
3. We have a huge number of standards today, many of which are of
immense value. But the most important ones have been developed
by harmonizing and tidying up the de facto standards. (014)
4. In 1991, I formulated a "Law of Standards" that keeps getting
more and more confirmation by every group that tries to develop
a so-called "proactive" standard: (015)
"Whenever a major organization develops a new system as an official
standard for X, the primary result is the widespread adoption of
some simpler system as a de facto standard for X." (016)
See http://www.jfsowa.com/computer/standard.htm (017)
Another confirmation of the law of standards: The W3C proposed OWL
as "The Web Ontology Language" and RDF triples for the data. The
results: (1) The overwhelming number of OWL ontologies published
on the WWW are limited to the subset of logic that Aristotle
defined for his syllogisms. (2) JSON has become the de facto
standard that programmers use instead of RDF. (3) The schema.org
proposed by Google, Microsoft, and Yahoo! uses JSON and Aristotle
instead of RDF and OWL. (018)
Recommendation: Instead of developing "proactive" standards for
ontology, I suggest that we note the law of standards: examine
what actually works, harmonize the best practices, and build the
new additions as extensions to the de facto standards. (019)
John
_________________________________________________________________ (020)
Source: http://www.jfsowa.com/talks/iss.pdf (021)
Slide 4: (022)
Size of the Problem
Some estimates:
● World-wide digital data in 2009: 800 million terabytes.
● Estimated digital data in 2010: 1.2 billion terabytes.
● Legacy software: Half a trillion lines of code.
● Percentage that is tagged with semantics: Slightly over 0% (023)
Slide 7: (024)
How Could Semantics Help?
Typical programmer productivity with current tools:
● 10 to 15 lines of fully debugged code per person per day.
● Cost per line of code: $18 to $45.
● Most of the time is spent on analysis, design, and testing.
● Specification errors are the most costly and time consuming
and the most likely to benefit from clearly defined semantics. (025)
Why semantic technology isn’t used more widely:
● Too much time, effort, and training to specify semantics.
● Delayed implementation without any obvious benefit.
● Difficulty of sharing semantics among different tools,
especially tools designed for different methodologies. (026)
We need better tools and better integration among tools. (027)
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