On 5/22/13 10:21 AM, John F Sowa wrote:
> Kingsley, Pat H, and Matthew,
>
> KI
>>> Relations are the fundamental mechanism for expressing Data.
>> Basically, Data Representation is all about encoding Relations.
>> This assumes that all observations boil down to perception
>> of relationships (relations) between entities.
> PH
>> I think that this is quite correct. Certainly, all known data
>> representation formalisms are based on this assumption
> I agree.
>
> MW
>> OK until the last bit. You seem to be equating relationships to
>> relations. Not a good move in my view.
> KI
>> Yes, I agree...I've opted to make a little comprise by being
>> a little lossy about Relations and Relationships.
> With good examples, you can be simple and accurate at the same time. (01)
Yes. (02)
>
> In a relational DB, for example, a relation is represented by
> a table and a relationship is one row of the table. In RDF,
> a relationship is a single triple, and a relation is the set
> of all the triples with the same relation name. (03)
Yes, but mapping that out isn't so easy, when you have an attention
challenged non technical audience as the target. For instance, many that
even work with RDF wouldn't instinctively associate the IRI in the
predicate role/slot of an RDF triple with relation name i.e., what
denotes the relation represented by said RDF 3-tuple. (04)
Likewise, deconstructing an RDBMS table to unveil it too is comprised of
3-tuples where: (05)
1. Table Name denotes Domain
2. Field/Column Name denotes Predicate
3. Field/Column data types supported by DBMS determine Range. (06)
>
> KI
>> I want to use this perspective to bridge RDF, RDF based Linked Data,
>> and Database Management systems.
> That's a worthy goal. I suggest that you add logic to that list,
> but do it in a way that is simple, accurate, and readable. (07)
I tend to stick with inverse functional and sameAs relation semantics
since they are relatively intuitive. Of course, many get tripped up by
sameAs expressing co-referents of IRIs etc. Anyway, in this case, the
examples are easier to make and demonstrate especially when you have
real RDF and RDBMS data at hand. (08)
>
> My recommendation is to use *both* Peirce's existential graphs
> and RDF. Pat Hayes gave a talk at ISWC09, where he said that
> RDF + negation in a style that is similar to Peirce's EGs can
> represent full first-order logic:
>
> http://videolectures.net/iswc09_hayes_blogic/
>
> The point that Pat was making is that the blank nodes in RDF
> represent existential quantifiers, two or more triples on the
> same surface have an implicit conjunction (and) among them.
> If you add negation (in a way that's similar to EGs), you
> get the full expressive power of Common Logic.
>
> Following is a talk I presented to an audience that had been
> brainwashed by predicate calculus. That kind of audience is
> hard to reach because you have to peel off a lot of complex
> verbiage before you can show how simple logic really is:
>
> http://www.jfsowa.com/talks/eguni.pdf
>
> For example, see slide 6, in which I show one of Peirce's graphs,
> which could be translated directly to RDF. Ordinary human beings
> can read the graph directly. But you have to translate it to
> predicate calculus before logicians can understand it. (09)
I'll take a look. (010)
>
> To go beyond RDF, Peirce and Pat noted that you only need to add
> an enclosure that negates the nested graph or subgraph. If you
> allow arbitrary depth of nesting, you get full FOL. (011)
Yes, Pat has been trying :-) (012)
Thanks! (013)
>
> John
>
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> (014)
-- (015)
Regards, (016)
Kingsley Idehen
Founder & CEO
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