The core of the SWI-Prolog package semweb is an
efficient main-memory RDF store written in C that is tightly integrated
with Prolog. It provides a fully logical predicate rdf/3
to query the RDF store efficiently by using multiple (currently 9)
indexes. In addition, SWI-Prolog provides libraries for reading and
writing XML/RDF and Turtle and a library that provides persistency using
a combination of efficient binary snapshots and journals.
Below, we describe a few usage scenarios that guides the current
design of this Prolog-based RDF store.
Application prototyping platform
Bundled with ClioPatria,
the store is an efficient platform for prototyping a wide range of
semantic web applications. Prolog, connected to the main-memory based
store is a productive platform for writing application logic that can be
made available through the SPARQL endpoint of ClioPatria, using an
application specific API (typically based on JSON or XML) or as an HTML
based end-user application. Prolog is more versatile than SPARQL, allows
composing of the logic from small building blocks and does not suffer
from the Object-relational impedance mismatch.
Data integration
The SWI-Prolog store is optimized for entailment on the
rdfs:subPropertyOf relation. The rdfs:subPropertyOf
relation is crucial for integrating data from multiple sources while
preserving the original richness of the sources because integration can
be achieved by defining the native properties as sub-properties of
properties from a unifying schema such as Dublin Core.
Dynamic data
This RDF store is one of the few stores that is primarily based on
backward reasoning. The big advantage of backward reasoning is
that it can much easier deal with changes to the database because it
does not have to take care of propagating the consequences. Backward
reasoning reduces storage requirements. The price is more reasoning
during querying. In many scenarios the extra reasoning using a main
memory will outperform the fetching the precomputed results from
external storage.
Prototyping reasoning systems
Reasoning systems, not necessarily limited to entailment reasoning,
can be prototyped efficiently on the Prolog based store. This includes‘what-if’reasoning,
which is supported by snapshot and
transaction isolation. These features, together with the
concurrent loading capabilities, make the platform well equiped to
collect relevant data from large external stores for intensive
reasoning. Finally, the
TIPC
package can be used to create networks of cooperating RDF based agents.
Streaming RDF
Transactions, snapshots, concurrent modifications and the database
monitoring facilities (see rdf_monitor/2)
make the platform well suited for prototyping systems that deal with
streaming RDF data.
