Optique: OBDA Solution for Big Data

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. Rodriguez-Muro, M. Roshchin, F. Savo, M. Schmidt, A. Soylu, A. Waaler, and D. Zheleznyakov

Revised Selected Papers of ESWC 2013 Satellite Events. Volume 7955 of Lecture Notes in Computer Science. 2013.

Accessing the relevant data in Big Data scenarios is increasingly difficult both for end-user and IT-experts, due to the volume, variety, and velocity dimensions of Big Data. This brings a high cost overhead in data access for large enterprises. For instance, in the oil and gas industry, IT-experts spend 30-70% of their time gathering and assessing the quality of data. The Optique project (http://www.optique-project.eu/) advocates a next generation of the well known Ontology-Based Data Access (OBDA) approach to address the Big Data dimensions and in particular the data access problem. The project aims at solutions that reduce the cost of data access dramatically.

   title = "Optique:  OBDA Solution for Big Data",
   year = "2013",
   author = "D. Calvanese and M. Giese and P. Haase and I. Horrocks and T.
Hubauer and Y. Ioannidis and E. Jiménez-Ruiz and E. Kharlamov and
H. Kllapi and J. Klüwer and M. Koubarakis and S. Lamparter and R.
Möller and C. Neuenstadt and T. Nordtveit and Ö.  Özcep
and M. Rodriguez-Muro and M. Roshchin and F. Savo and M. Schmidt and A.
Soylu and A. Waaler and D. Zheleznyakov",
   booktitle = "Revised Selected Papers of ESWC 2013 Satellite Events",
   pages = "293--295",
   volume = "7955",
   publisher = "Springer",
   series = "Lecture Notes in Computer Science",
   doi = "10.1007/978-3-642-41242-4_48",
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