Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo

S. Brandt; C. Neuenstadt; Ö. Özçep; C. Pinkel; D. Zheleznyakov; I. Horrocks; R. Möller; Evgeny Kharlamov; Ernesto Jiménez-Ruiz; Yannis Kotidis; Steffen Lamparter; Theofilos Mailis; Ahmet Soylu; Christoforos Svingos; Yannis Ioannidis; Arild Waaler; Martin Giese

doi:10.1145/2933267.2933290

Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo

S. Brandt, C. Neuenstadt, Ö. Özçep, C. Pinkel, D. Zheleznyakov, I. Horrocks, R. Möller, Evgeny Kharlamov, Ernesto Jiménez-Ruiz, Yannis Kotidis, Steffen Lamparter, Theofilos Mailis, Ahmet Soylu, Christoforos Svingos, Yannis Ioannidis, Arild Waaler, Martin Giese

Institute of Information Systems

Abstract

Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work, we show how Semantic Technologies implemented in our system OPTIQUE can simplify such complex diagnostics by providing an abstraction layer- ontology-that integrates heterogeneous data. In a nutshell, OPTIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries, which can be easily formulated with our visual query formulation system. OPTIQUE can then automatically enrich these queries, translate them into a large collection of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment. © 2016 ACM.

Original language	English
Title of host publication	Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems
Number of pages	4
Place of Publication	New York, NY, USA
Publisher	ACM
Publication date	13.06.2016
Pages	350-353
ISBN (Print)	978-1-4503-4021-2
DOIs	https://doi.org/10.1145/2933267.2933290
Publication status	Published - 13.06.2016
Event	10th ACM International Conference on Distributed and Event-Based Systems - Beckman Center of the National Academies of Sciences and Engineering, Irvine, United States Duration: 20.06.2016 → 24.06.2016 Conference number: 122247

DFG Research Classification Scheme

409-06 Information Systems, Process and Knowledge Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/2933267.2933290

Cite this

Brandt, S., Neuenstadt, C., Özçep, Ö., Pinkel, C., Zheleznyakov, D., Horrocks, I., Möller, R., Kharlamov, E., Jiménez-Ruiz, E., Kotidis, Y., Lamparter, S., Mailis, T., Soylu, A., Svingos, C., Ioannidis, Y., Waaler, A., & Giese, M. (2016). Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo. In Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems (pp. 350-353). (International Conference on Distributed and Event-Based Systems). ACM. https://doi.org/10.1145/2933267.2933290

@inproceedings{fda5fd52a217447b861888039b6a1320,

title = "Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo",

abstract = "Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work, we show how Semantic Technologies implemented in our system OPTIQUE can simplify such complex diagnostics by providing an abstraction layer- ontology-that integrates heterogeneous data. In a nutshell, OPTIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries, which can be easily formulated with our visual query formulation system. OPTIQUE can then automatically enrich these queries, translate them into a large collection of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment. {\textcopyright} 2016 ACM.",

author = "S. Brandt and C. Neuenstadt and {\"O}. {\"O}z{\c c}ep and C. Pinkel and D. Zheleznyakov and I. Horrocks and R. M{\"o}ller and Evgeny Kharlamov and Ernesto Jim{\'e}nez-Ruiz and Yannis Kotidis and Steffen Lamparter and Theofilos Mailis and Ahmet Soylu and Christoforos Svingos and Yannis Ioannidis and Arild Waaler and Martin Giese",

year = "2016",

month = jun,

day = "13",

doi = "10.1145/2933267.2933290",

language = "English",

isbn = "978-1-4503-4021-2",

series = "International Conference on Distributed and Event-Based Systems",

publisher = "ACM",

pages = "350--353",

booktitle = "Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems",

note = "10th ACM International Conference on Distributed and Event-Based Systems, DEBS 2016 ; Conference date: 20-06-2016 Through 24-06-2016",

}

Brandt, S, Neuenstadt, C, Özçep, Ö, Pinkel, C, Zheleznyakov, D, Horrocks, I, Möller, R, Kharlamov, E, Jiménez-Ruiz, E, Kotidis, Y, Lamparter, S, Mailis, T, Soylu, A, Svingos, C, Ioannidis, Y, Waaler, A & Giese, M 2016, Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo. in Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems. International Conference on Distributed and Event-Based Systems, ACM, New York, NY, USA, pp. 350-353, 10th ACM International Conference on Distributed and Event-Based Systems, Irvine, California, United States, 20.06.16. https://doi.org/10.1145/2933267.2933290

Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo. / Brandt, S.; Neuenstadt, C.; Özçep, Ö. et al.
Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems. New York, NY, USA: ACM, 2016. p. 350-353 (International Conference on Distributed and Event-Based Systems).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

TY - GEN

T1 - Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo

AU - Brandt, S.

AU - Neuenstadt, C.

AU - Özçep, Ö.

AU - Pinkel, C.

AU - Zheleznyakov, D.

AU - Horrocks, I.

AU - Möller, R.

AU - Kharlamov, Evgeny

AU - Jiménez-Ruiz, Ernesto

AU - Kotidis, Yannis

AU - Lamparter, Steffen

AU - Mailis, Theofilos

AU - Soylu, Ahmet

AU - Svingos, Christoforos

AU - Ioannidis, Yannis

AU - Waaler, Arild

AU - Giese, Martin

N1 - Conference code: 122247

PY - 2016/6/13

Y1 - 2016/6/13

N2 - Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work, we show how Semantic Technologies implemented in our system OPTIQUE can simplify such complex diagnostics by providing an abstraction layer- ontology-that integrates heterogeneous data. In a nutshell, OPTIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries, which can be easily formulated with our visual query formulation system. OPTIQUE can then automatically enrich these queries, translate them into a large collection of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment. © 2016 ACM.

AB - Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work, we show how Semantic Technologies implemented in our system OPTIQUE can simplify such complex diagnostics by providing an abstraction layer- ontology-that integrates heterogeneous data. In a nutshell, OPTIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries, which can be easily formulated with our visual query formulation system. OPTIQUE can then automatically enrich these queries, translate them into a large collection of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment. © 2016 ACM.

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-84978636796&origin=inward&txGid=086015d368bfac84319e6e8ca0e69ed6

U2 - 10.1145/2933267.2933290

DO - 10.1145/2933267.2933290

M3 - Conference contribution

SN - 978-1-4503-4021-2

T3 - International Conference on Distributed and Event-Based Systems

SP - 350

EP - 353

BT - Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems

PB - ACM

CY - New York, NY, USA

T2 - 10th ACM International Conference on Distributed and Event-Based Systems

Y2 - 20 June 2016 through 24 June 2016

ER -

Brandt S, Neuenstadt C, Özçep Ö, Pinkel C, Zheleznyakov D, Horrocks I et al. Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo. In Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems. New York, NY, USA: ACM. 2016. p. 350-353. (International Conference on Distributed and Event-Based Systems). doi: 10.1145/2933267.2933290

Enabling Semantic Access to Static and Streaming Distributed Data with Optique: Demo

Abstract

DFG Research Classification Scheme

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this