The following are the projects in which I’m currently involved:
- Helix – Helix platform includes a novel, data-format agnostic indexing mechanism, and light-weight data linking techniques that could link semantically related records across internal and external data sources of various characteristics.
- -ontop- I am the coordinator and main developer of the -ontop- for Ontology Based Data Access. A Java framework that includes utilities to write and read mappings (e.g., R2RML, D2RQ, etc.), to manipulate mappings, a plugin for Protege 4.x and a reasoner called Quest. Quest allows implements all reasoning techniques we developed in the last years and as a result, is one of the most efficient tools for OWL 2 QL reasoning and for querying virtual RDF graphs with SPARQL. It is able to deal with very large amounts of data (GB and TBs) by reusing SQL in very efficient ways. To learn more about -ontop and Quest visit the official website.
- Optique Optique is a large-scale integrating project (IP) of the FP7 framework. The objective of Optique is to bring about a paradigm shift for data access by i) providing a semantic end-to-end connection between users and data sources ii) enabling users to rapidly formulate intuitive queries using familiar vocabularies and conceptualisations ii) seamlessly integrating data spread across multiple distributed data sources, including streaming sources iii) exploiting massive parallelism for scalability far beyond traditional RDBMSs and thus reducing the turnaround time for information requests to minutes rather than days. To know more about about Optique, please visit the official website. -ontop- is a central component in the Optique project, and starting from November 2012, the development of -ontop- is financed by the Optique.
- TONES. 3 year STREP FET project Financed within the EU 6th Framework Programme under contract number FP6-7603.
The aim of the project was study and develop automated reasoning techniques for both offline and online tasks associated with ontologies. My role in TONES was to investigate the use of ontologies and data, in particular, to explore Ontology Based Data Access performance issues. I did this work mostly on top of the QuOnto/Mastro system (see bellow) in the context of my Ph.D. thesis.
- QuOnto/Mastro. A reasoner for the Description logic DL-Lite that provides query answering over ontologies. I was working mostly on the optimization of the performance of Mastro(i), the layer on top of QuOnto that handles the definition of “Virtual ABoxes” that are connected to the ontology’s vocabulary by means of mappings. I focused on the strong connection between SQL structure/redundancy and performance in query-rewriting based approaches to query answering on top of RDBMS. The lesons learned during this work are now being applied in my current projects, mainly in -ontop- and Optique (see above).