v1.8 now available

We are happy to announce the availability of

-ontop- v1.8

a Java framework to query RDBMS using SPARQL over RDF(s) and OWL ontologies.

If you are interested in virtual RDF graphs, R2RML mappings and/or RDFS/OWL2QL reasoning, then -ontop- is for you. The system implements the cutting edge SPARQL-to-SQL and query optimisation techniques that allow it to answer SPARQL queries using SQL databases while obtaining great performance.

With -ontop-, you don't need to move your data from your DB to enjoy the benefits of the RDF data model, the SPARQL query language or RDF/OWL2QL inference. There is no need for expensive ETL or forward/backward chaining either.

The project went through a large refactoring (its still ongoing) and this is our most stable release to the date. Moreover, as always, we included many new features. The highlights of this new release include:

• SOURCE CODE IS NOW AVAILABLE (See the new license terms)
• Improved mapping syntax (see full changelog)
• New command line tools to query, automatically generate mappings, generate RDF/OWL from mappings
• Faster SQL translation
• Improved the SQL queries generated by Quest by avoiding some operations when unnecessary (e.g., casting), and placing optimally the JOIN conditions in the SQL query. 
• Major restructuring of code for performance and clarity of the API (this is still ongoing)
• Many important bugfixes for CONSTRUCT, ASK and DESCRIBE queries -ontopPro- is now compatible with Protege 4.3
• Many bug fixes

Cheers,
The -ontop- development team

Build 2305 is available

The highlights of this new release include:

* Support for importing/exporting R2RML mappings
* Support for automated mapping generation as defined by the "Direct Mapping" W3C specification
* Various options for data materialization (similar to dump-rdf in D2RQ)
* Support for concurrent queries in the SPARQL endpoint through connection pooling
* Better support for Oracle, Postgres, SQL Server and DB2
* Improved the SQL queries generated by Quest by avoiding some operations when unnecessary (e.g., casting), and placing optimally the JOIN conditions in the SQL query.

New build on the oven

Following last release, we have been cooking the next release. Goodies to expect in this release are:

• Support for multiple JDBC connections by connection pooling, which means better performance in multithreaded environments.
• Support for multiple clients for the SPARQL end-point (btw, we are getting GREAT performance in comparison to single client benchmarks)
• First implementation of R2RML and Direct Mapping! yes, finally. There are still some rough edges, but most of it is already there. Documentations on how to use these will come with the release.
• Several important bug-fixes for DB2 and SQL Server.

We are also running many new benchmarks, comparing OWLIM, Virtuoso, Stardog, D2RQ, Sparqlmap and Quest using several DBs as backend (MySQL, PostgreSQL, DB2), we'll start putting the results online as soon as possible. So far, things look good for Quest and -ontop-, even when using open source DBs such as MySQL.

New build almost ready, great performance enhancements

Quick update, we are now preparing the next build. We are quite excited since we finally finished implementing several optimization that where missing on the mapping manipulation algorithm. The use of "OR" in WHERE clauses is much more robust now and we now are able to exploit FOREIGN KEY contraints.

The result is that in virtual RDF Graph mode, with real databases and usual SPARQL queries we rarely generate more than 1 query SQL query one which often matches what you would have written yourself in SQL. An it is FAST (also for more complex SPARQL with variables everywhere, even if its more than one query), even with inference enabled.

We'll be posting benchmark numbers soon. Stay tunned!

Documentation and Examples

Quick update. He have re-organized the documentation section of the main site and of the technical wiki . Things should be much easier to find now.

We are also extending the "Examples" section with several of the scenarios that we use for testing, demonstration and benchmarking. We have already included the BSBM and FishMark scenarios that we use for benchmarks, and the IMDB-MovieOntology scenario that we use for demonstrations. Take a look at them, they are nice examples of very natural mappings.

The IMDB-MovieOntology scenario is particularly interesting since the database is real, very large and mappings turn out to be interesting. Take a look!

New build available! Tons of new features!

We are happy to announce the availability of a new build 2039 of -ontop- v1.7-alpha, a Java framework to query RDFS/OWL2QL ontologies with mappings to databases. The SPARQL engine, Quest, implements the latests techniques in SPARQL-to-SQL rewriting, produces very fast SQL queries and supports inference out of the box.

The framework is still in alpha and has several rough edges, however, given the performance it is currently able to deliver, and that many features are already stable, we think it might be interesting to give it a test drive. Please help us improve the stability of the build and bring it to beta grade and report any issues you encounter, we'll take all your feedback into account for the next release.

This upgrade includes bug fixes, major improvements to existing features and many new and exciting features. Some of the highlights of this build include:

SPARQL 1.0 support:

• Support for most SPARQL built in functions, e.g., arithmetics, type checking, etc.
• Support for CONSTRUCT and DESCRIBE result forms.
• Support for OPTIONAL and bound, which allow you to have NEGATION in the usual SPARQL 1.0 style.
• Support for variables in ANY position, e.g., to allow queries such as SELECT ?p ?v WHERE { ?x :name "John Smith". ?x ?p ?v }
• Stronger compliance to standard RDF and SPARQL semantics for FILTER expressions.

Performance

• Multiple improvements to the SPARQL-to-rule translation, mapping and TBox optimization algorithms.
• New algorithm for query rewriting w.r.t. the TBox that increases the performance of query answering by many orders of magnitude when inference w.r.t. to existential constants is enabled. The implementation has been contributed by Dr. Roman Kontchakov.
• Benchmarks. We finally started work on benchmarking. We tested against Virtuoso triple store, Virtuoso RDF views and D2R Server using the BSBM and FishMark benchmarks. The results show that Quest's query answering technique for 'virtual RDF graphs' can outperform these systems, in some cases by several orders of magnitude even when using an open source database as the backend. 

APIs and Accessibility

• Completely new Sesame API provider, now users of Sesame can create "Virtual RDF repositories" with -ontop-.
• SPARQL end-point support through integration with Sesame's workbench.

Mapping language

• Improved support for default literal types, now it conforms with the R2RML "Natural Mapping" specification.
• Support for language tags obtained from the DB
• Proper support for constants in the mappings
• Proper internal handling of NULL values in the database (as recommended by the R2RML standard)

Database support

• Restored support for Oracle, DB2 and SQL Server
• Improved support and performance over MySQL

Documentation

• Revised and extended all technical documentation

The new build can be downloaded from our brand new website:

     http://ontop.inf.unibz.it/


Happy new year!
The -ontop- Team

Optique starts!

Last week we were in Oslo for the kick-off meeting of Optique. For those that don't know yet, Optique [1] is the EU project that will be funding research for and the development of -ontop- for the next 4 years.
The objective of the project (in simpler words that those used in the brochures) is to use semantic technology, with focus on reasoning and OBDA, to create an integrated solution that companies can use to regain control of their data. The keyword here is Big Data, big in volume of course, but also in diversity and speed.

The basic idea is that RDF, Ontology and OBDA can allow companies to perform complex data integration tasks in cheaper ways and through methodologies that will allow them to continue growing in a controlled way.

The consoritium is made by a great bunch of bright people, which are very much eager to deliver the promised results.

On the academic side the consortium includes of course the Free University  of Bolzano, but also University of Athens, Oxford University, Technical University of Hamburg, University of Oslo and Sapienza University of Rome.

On the industrial side things are also very exciting. Working on the integration of results and making a real product out of the things academic do we will have FuildOps, and specialised in the Statoil use case we will also have DNV. And something very exciting about the industry side is that we will have Siemens and Statoil too as providers for use cases, consumers and evaluators of the technology developed within the project. In both cases we are talking abouta huge number of data sources and ridiculous volumes of data.

What is extremely exciting about all this is that -ontop- and Quest are going to be central in achieving all this goals, we are all betting on efficient query rewriting and efficient execution. Because of that, we are getting funding of course and thanks to that we already grew the team from 2 people actively developing -ontop- to 4 people, and we will grow to 5 or 6 very soon. More over, we started already focusing a lot in things related to usability in order to be able to integrate with the tools from FluidsOp and to be ready to start providing results in the first months. Things are moving fast, and will move even faster in 2013.

In conclusion,  things are going to get really exciting in the OBDA are, so stay tuned!

[1] http://optique.project.ifi.uio.no/ (temporal website)