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来自牛津大学的大数据研究项目,注:国外的研究项目一般都有一个很好的站点反映研究状态及进展信息。
Optique: Scalable End-user Access to Big Data
Scalable enduser 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: (i) 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; (ii) Integrate distributed heterogeneous sources, including streams; (iii) Exploit massively parallel technologies and holistic optimisations to maximise performance; (iv) Include tools to support query formulation and ontology and mapping management; and (v) Use 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 sets.
Links
Capturing Model−Based Ontology Evolution at the Instance Level: The Case of DL−Lite Evgeny Kharlamov‚ Dmitriy Zheleznyakov and Diego Calvanese In Journal of Computer and System Sciences (JCSS). Vol. 79. No. 6. Pages 835 − 872. 2013. |
Towards Query Formulation and Query−Driven Ontology Extensions in OBDA Bernardo Cuenca Grau‚ Martin Giese‚ Ian Horrocks‚ Thomas Hubauer‚ Ernesto Jiménez−Ruiz‚ Evgeny Kharlamov‚ Michael Schmidt‚ Ahmet Soylu and Dmitriy Zheleznyakov In OWL Experiences and Directions Workshop (OWLED). 2013. |
The Optique Project: Towards OBDA Systems for Industry (Short Paper) D. Calvanese‚ M. Giese‚ P. Haase‚ I. Horrocks‚ T. Hubauer‚ Y. Ioannidis‚ E. Jiménez−Ruiz‚ E. Kharlamov‚ H. Kllapi‚ J. Klüwer‚ M. Koubarakis‚ S. Lamparter‚ R. Möller‚ C. Neuenstadt‚ T. Nordtveit‚ Ö. Özcep‚ M. driguez−Muro‚Ro M. Roshchin‚ Marco Ruzzi‚ F. Savo‚ M. Schmidt‚ A. Soylu‚ A. Waaler and D. Zheleznyakov In OWL Experiences and Directions Workshop (OWLED). 2013. |
Sponsors
info
Duration | 1st November 2012 to 31st October 2016 |
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