Optique: Scalable End-user Access to Big Data
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: (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.
Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo
Evgeny Kharlamov‚ Sebastian Brandt‚ Martin Giese‚ Ernesto Jiménez−Ruiz‚ Yannis Kotidis‚ Steffen Lamparter‚ Theofilos Mailis‚ Christian Neuenstadt‚ Özgür L. Özçep‚ Christoph Pinkel‚ Ahmet Soylu‚ Christoforos Svingos‚ Dmitriy Zheleznyakov‚ Ian Horrocks‚ Yannis E. Ioannidis‚ Ralf Möller and Arild Waaler
In Proc. International Conference on Distributed and Event−based Systems (DEBS). Pages 350–353. 2016.
Ontology−Based Integration of Streaming and Static Relational Data with Optique
Evgeny Kharlamov‚ Sebastian Brandt‚ Ernesto Jiménez−Ruiz‚ Yannis Kotidis‚ Steffen Lamparter‚ Theofilos Mailis‚ Christian Neuenstadt‚ Özgür L. Özçep‚ Christoph Pinkel‚ Christoforos Svingos‚ Dmitriy Zheleznyakov‚ Ian Horrocks‚ Yannis E. Ioannidis and Ralf Möller
In Proc. of International Conference on Management Data (SIGMOD). Pages 2109–2112. 2016.
Ontology−based Visual Query Formulation: An Industry Experience
Ahmet Soylu‚ Evgeny Kharlamov‚ Dmitriy Zheleznyakov‚ Ernesto Jimenez−Ruiz‚ Martin Giese and Ian Horrocks
In Proc. of International Symposium on Visual Computing (ISVC). Springer. 2015.