Scalable end-user access to Big Data is essential for the effective support of critical decision making in large companies. The Optique project aims to develop new techniques and infrastructure that will bring about a paradigm shift for data access by:
- using Ontology Based Data Access (OBDA) to provide a semantic end-to-end connection between users and data sources;
- enabling users to rapidly formulate intuitive queries using familiar vocabularies and conceptualisations;
- seamlessly integrating data spread across multiple distributed data sources, including streaming sources;
- exploiting massive parallelism for scalability far beyond traditional RDBMSs;
and thus reducing the turnaround time for information requests to minutes rather than days.
These objectives will be achieved by bringing together leading researchers
and developers from diverse communities — including Knowledge Representation, Databases, and the Semantic Web — to devise new techniques and to implement them in an
extensible platform that will provide a complete and generic solution
to the data access challenges posed by Big Data.
The platform will:
- Use an ontology and declarative mappings to
capture user conceptualisations and to transform user queries into
complete, correct and highly optimised queries over the data sources;
- Integrate distributed heterogeneous sources, including streams;
- Exploit massively parallel technologies and holistic
optimisations to maximise performance;
- Include tools to support
query formulation and ontology and mapping management;
semi-automatic bootstrapping of ontologies and mappings and query
driven ontology construction to minimise installation overhead.
Development of the platform will be informed by and continuously
evaluated against the requirements of complex real-world challenges,
with two large European companies providing the project with
comprehensive use cases, and access to user groups and TB scale data
Optique project has received funding from the European Union's Seventh Framework Programm for research, technological development and demonstration under grant agreement no 318338.
Héctor Pérez-Urbina, Boris Motik, and Ian Horrocks.
Tractable Query Answering and Rewriting under Description Logic Constraints
J. of Applied Logic, 8(2):186-209, 2010.
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Boris Motik, Bernardo Cuenca Grau, Ian Horrocks, Zhe Wu, Achille Fokue and Carsten Lutz (eds.).
OWL 2 Web Ontology Language Profiles.
W3C Recommendation, 27 October 2009.
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