Kingsley, Pat H, and Matthew, (01)
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. (02)
PH
> I think that this is quite correct. Certainly, all known data
> representation formalisms are based on this assumption (03)
I agree. (04)
MW
> OK until the last bit. You seem to be equating relationships to
> relations. Not a good move in my view. (05)
KI
> Yes, I agree...I've opted to make a little comprise by being
> a little lossy about Relations and Relationships. (06)
With good examples, you can be simple and accurate at the same time. (07)
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. (08)
KI
> I want to use this perspective to bridge RDF, RDF based Linked Data,
> and Database Management systems. (09)
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. (010)
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: (011)
http://videolectures.net/iswc09_hayes_blogic/ (012)
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. (013)
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: (014)
http://www.jfsowa.com/talks/eguni.pdf (015)
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. (016)
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. (017)
John (018)
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