Hello Richard
Well, I was trying to do that for a rather big ontology - I'm ballparking
here, but I think that, after dumping the RDF, I would have over 1,000,000
assertions, and would easily double that adding inferred knowledge. The
source databases are updated daily, but I could live with weekly refreshing
the ontology and inferring knowledge.
I would benefit of some incremental approach for that. Is there some option
of rdf-dump for specifiying some condition on data that is dumped?
I also noticed that there are rdf-dump results contains a lot of replicated
triples. Am I doing something wrong?
Diogo F.C. Patrão
Manager of Medical Informatics
Biotechnology Laboratory
Hospital A.C. Camargo
http://www.accamargo.org.br/
On Mon, Jan 24, 2011 at 9:24 AM, Richard Cyganiak <[email protected]>wrote:
> Hi Diogo,
>
> There are a number of different ways how you can do inference over a D2RQ
> model but none of them work very well. In practice, if your data doesn't
> change too often then the easiest route is replicating the database into a
> triple store that supports inference.
>
> I'm not aware of any out-of-the-box approach that works without replicating
> the data *and* performs well.
>
> The easiest way of getting at least some limited inference would be to
> simply modify the D2RQ mapping file to add some additional d2rq:class and
> d2rq:property statements. This can cover at least RDFS inference (domain,
> range, subClassOf, subPropertyOf), and some bits of OWL (equivalentClass,
> equivalentProperty, some cases of union and intersection, perhaps more).
>
> If you only need this to work for a single small ontology, then you could
> do that by hand. The general approach would be to automate it -- write some
> code that reads the ontology, reads the D2RQ mapping, and then augments the
> D2RQ mapping with the appropriate additional constructs. This could probably
> be written in a rules language.
>
> I'd be happy to help a bit with this.
>
> Best,
> Richard
>
>
> On 14 Jan 2011, at 20:37, Diogo FC Patrao wrote:
> > My doubt concerns the piece of code found on the page below, section
> 5.3.2.
> >
> > http://sws.ifi.uio.no/semdays2010/05exercises.html
> >
> > It simply loads a d2r mapping file, a owl ontology, and answers a sparql
> query doing inference with pellet (based on rules and axioms present on the
> owl ontology). d2r mapping points to a mysql database in my desktop, with 4
> fields, 3 of them indexed.
> >
> > So far so good. However, when it does:
> >
> > 34: Model d2rData = new ModelD2RQ(readModel(d2r), null);
> > 45: ontModel.add(d2rData);
> >
> >
> > I think it dumps all data from d2rq and then adds it to the ontology
> model. That's undesirable, because it took 2G of ram to load, and 5 minutes
> to run a rather simple query:
> >
> > SELECT DISTINCT *
> > {
> > ?s a vocab:pacienteCabecaEPescocoEstadio0.
> > } limit 10
> >
> >
> > and this class is equivalent to two other classes. I got 8 results, from
> 3000 instances total.
> >
> >
> > What I would like to do is to reduce the querying time, and reduce memory
> consumption (in this order).
> >
> > Is there another way to write this code to access d2rq, instead of
> dumping all data? I mean, I don't know the internals of pellet, but querying
> the sparql endpoint generated by d2r-server for the expanded query (like
> above, but specifying the two classes) is so much faster.
> >
> > If there isn't, I would like to improve the code so it would be like a
> server, loading once and answering queries. Would d2r data be out of sync
> after the mapped database is updated?
> >
> > Where do I go now?
> >
> > Thanks!!
> >
> >
> >
> >
> > Diogo F.C. Patrão
> > Manager of Medical Informatics
> > Biotechnology Laboratory
> > Hospital A.C. Camargo
> > http://www.accamargo.org.br/
> >
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