%0 Conference Paper %1 kharlamov16towardsISWC16 %A Kharlamov, Evgeny %A Kotidis, Yannis %A Mailis, Theofilos %A Neuenstadt, Christian %A Nikolaou, Charalampos %A Özcep, Özgür L. %A Svingos, Christoforos %A Zheleznyakov, Dmitriy %A Brandt, Sebastian %A Horrocks, Ian %A Ioannidis, Yannis E. %A Lamparter, Steffen %A Möller, Ralf %B The Semantic Web - ISWC 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17-21, 2016, Proceedings, Part II %D 2016 %E Groth, Paul T. %E Simperl, Elena %E Gray, Alasdair J. G. %E Sabou, Marta %E Krötzsch, Markus %E Lécué, Freddy %E Flöck, Fabian %E Gil, Yolanda %K OBDA optique-project %P 344--362 %R 10.1007/978-3-319-46547-0_31 %T Towards Analytics Aware Ontology Based Access to Static and Streaming Data %U http://dx.doi.org/10.1007/978-3-319-46547-0_31 %V 9982 %X Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data.

@inproceedings{kharlamov16towardsISWC16, abstract = {Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data.}, added-at = {2016-10-11T11:27:20.000+0200}, audience = {academic}, author = {Kharlamov, Evgeny and Kotidis, Yannis and Mailis, Theofilos and Neuenstadt, Christian and Nikolaou, Charalampos and Özcep, Özgür L. and Svingos, Christoforos and Zheleznyakov, Dmitriy and Brandt, Sebastian and Horrocks, Ian and Ioannidis, Yannis E. and Lamparter, Steffen and Möller, Ralf}, bibsource = {dblp computer science bibliography, http://dblp.org}, biburl = {https://www.bibsonomy.org/bibtex/24e85e22c3819272c249e322f381efeec/oezcep}, booktitle = {The Semantic Web - {ISWC} 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17-21, 2016, Proceedings, Part {II}}, date-added = {2016-10-11 09:15:40 +0000}, date-modified = {2016-10-11 09:15:40 +0000}, doi = {10.1007/978-3-319-46547-0_31}, editor = {Groth, Paul T. and Simperl, Elena and Gray, Alasdair J. G. and Sabou, Marta and Kr{\"{o}}tzsch, Markus and L{\'{e}}cu{\'{e}}, Freddy and Fl{\"{o}}ck, Fabian and Gil, Yolanda}, interhash = {1861af957de6c481e190213306fa48c3}, intrahash = {4e85e22c3819272c249e322f381efeec}, keywords = {OBDA optique-project}, openaccess = {No}, pages = {344--362}, partneroptique = {UOXL}, series = {Lecture Notes in Computer Science}, timestamp = {2016-12-08T10:39:57.000+0100}, title = {Towards Analytics Aware Ontology Based Access to Static and Streaming Data}, url = {http://dx.doi.org/10.1007/978-3-319-46547-0_31}, volume = 9982, wpoptique = {WP5}, year = 2016, yearoptique = {Y4} }