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Reference: Evgeny Kharlamov, Nina Solomakhina, Özgür Özçep et al., How semantic technologies can enhance data access at Siemens Energy. (2014). The Semantic Web – ISWC 2014 : 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part I. 601-619.Citable link to this page:

 

How semantic technologies can enhance data access at Siemens Energy

Abstract: We present a description and analysis of the data access challenge in the Siemens Energy. We advocate for Ontology Based Data Access (OBDA) as a suitable Semantic Web driven technology to address the challenge. We derive requirements for applying OBDA in Siemens, review existing OBDA systems and discuss their limitations with respect to the Siemens requirements. We then introduce the Optique platform as a suitable OBDA solution for Siemens. Finally, we describe our preliminary installation and evaluation of the platform in Siemens.

Publication status:PublishedPeer Review status:Peer reviewedVersion:Accepted ManuscriptDigital Origin:Born digital Funder: EU-FP7   Notes:© Springer International Publishing Switzerland. The final publication is available athttp://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_38

Bibliographic Details

Publisher: Springer International Publishing

Publisher Website: http://www.springer.com/

Host: The Semantic Web – ISWC 2014 : 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part Isee more from them

Issue Date: 2014

Copyright Date: 2014

pages:601-619Identifiers

Doi: https://doi.org/10.1007/978-3-319-11964-9_38

Issn: 0302-9743

Isbn: 978-3-319-11963-2

Urn: uuid:63961fe6-3bae-454c-af18-2d323f5a626e Item Description

Type: Book (monograph): Section of book or chapter of book;

Language: en

Version: Accepted ManuscriptKeywords: OBDA ontology Optique data access use case descriptionSubjects: Computing Program development and tools Tiny URL: ora:9496

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Author: Dr Evgeny Kharlamov - websitehttp:-www.cs.ox.ac.uk-people-evgeny.kharlamov- institutionUniversity of Oxford facultyMathematical,

Source: https://ora.ox.ac.uk/objects/uuid:63961fe6-3bae-454c-af18-2d323f5a626e



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