An inference engine for RDF - Agfa

An inference engine for RDF
Fig.1.1. A Semantic Web case study
The travel agent agrees with the client about the itinerary: by train from
Antwerp to Brussels, by airplane from Brussels to Nice and by train from Nice
to St. Tropez. This still leaves room for some alternatives. The client will come
back to make a final decision once the travel agent has said him by mail that he
has worked out some alternative solutions like price for first class vs second
class etc...
Remark that the decision for the itinerary that has been taken is not very well
founded; only very crude price comparisons have been done based on some
internet sites that the travel agent consulted during his conversation with the
client. A very cheap flight from Antwerp to Cannes has escaped the attention of
the travel agent.
The travel agent will now further consult the internet sites of the Belgium
railways, the Brussels airport and the France railways to get some alternative
prices, departure times and total travel times.
Now let’ s compare this with the hypothetical situation that a full blown
Semantic Web would exist. In the computer of the travel agent resides a
Semantic Web agent that has at its disposal all the necessary standard tools. The
travel agent has a specialised interface to the general Semantic Web agent. He
fills in a query in his specialised screen. This query is translated to a
standardised query format for the Semantic Web agent. The agent consult his
rule database. This database of course contains a lot of rules about travelling as
well as facts like e.g. facts about internet sites where information can be
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