Distributed semantic analytics using the SANSA stack

Jens Lehmann; Gezim Sejdiu; Lorenz Bühmann; Patrick Westphal; Claus Stadler; Ivan Ermilov; Simon Bin; Nilesh Chakraborty; Muhammad Saleem; Axel Cyrille Ngonga Ngomo; Hajira Jabeen

doi:10.1007/978-3-319-68204-4_15

Distributed semantic analytics using the SANSA stack

Jens Lehmann^*
, Gezim Sejdiu
, Lorenz Bühmann
, Patrick Westphal
, Claus Stadler
, Ivan Ermilov
, Simon Bin
, Nilesh Chakraborty
, Muhammad Saleem
, Axel Cyrille Ngonga Ngomo
, Hajira Jabeen

^*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

63 Zitate (Scopus)

Abstract

A major research challenge is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and reasoning. Analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases, and most analytics approaches which do scale horizontally (i.e., can be executed in a distributed environment) work on simple feature-vector-based input. This software framework paper describes the ongoing Semantic Analytics Stack (SANSA) project, which supports expressive and scalable semantic analytics by providing functionality for distributed computing on RDF data.

Originalsprache	Englisch
Titel	The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings
Redakteure/-innen	Miriam Fernandez, Claudia d’Amato, Valentina Tamma, Philippe Cudre-Mauroux, Freddy Lecue, Christoph Lange, Juan Sequeda, Jeff Heflin
Seitenumfang	9
Herausgeber (Verlag)	Springer-Verlag Austria
Erscheinungsdatum	2017
Seiten	147-155
ISBN (Print)	9783319682037
DOIs	https://doi.org/10.1007/978-3-319-68204-4_15
Publikationsstatus	Erschienen - 2017
Extern publiziert	Ja
Veranstaltung	16. Internationale Semantic-Web-Konferenz, ISWC 2017 - Vienna, Österreich Dauer: 21.10.2017 → 25.10.2017 Konferenznummer: 16

Bibliographische Notiz

Publisher Copyright:
© Springer International Publishing AG 2017.

Fachgebiete und Schlagwörter

Informatik

ASJC Scopus Sachgebiete

Theoretische Informatik
Allgemeine Computerwissenschaft

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10.1007/978-3-319-68204-4_15

Dieses zitieren

Lehmann, J., Sejdiu, G., Bühmann, L., Westphal, P., Stadler, C., Ermilov, I., Bin, S., Chakraborty, N., Saleem, M., Ngonga Ngomo, A. C., & Jabeen, H. (2017). Distributed semantic analytics using the SANSA stack. in M. Fernandez, C. d’Amato, V. Tamma, P. Cudre-Mauroux, F. Lecue, C. Lange, J. Sequeda, & J. Heflin (Hrsg.), The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings (S. 147-155). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 10588 LNCS). Springer-Verlag Austria. https://doi.org/10.1007/978-3-319-68204-4_15

Lehmann, Jens ; Sejdiu, Gezim ; Bühmann, Lorenz et al. / Distributed semantic analytics using the SANSA stack. The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings. Hrsg. / Miriam Fernandez ; Claudia d’Amato ; Valentina Tamma ; Philippe Cudre-Mauroux ; Freddy Lecue ; Christoph Lange ; Juan Sequeda ; Jeff Heflin. Springer-Verlag Austria, 2017. S. 147-155 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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author = "Jens Lehmann and Gezim Sejdiu and Lorenz B{\"u}hmann and Patrick Westphal and Claus Stadler and Ivan Ermilov and Simon Bin and Nilesh Chakraborty and Muhammad Saleem and \{Ngonga Ngomo\}, \{Axel Cyrille\} and Hajira Jabeen",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 16th International Semantic Web Conference, ISWC 2017 ; Conference date: 21-10-2017 Through 25-10-2017",

year = "2017",

doi = "10.1007/978-3-319-68204-4\_15",

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Lehmann, J, Sejdiu, G, Bühmann, L, Westphal, P, Stadler, C, Ermilov, I, Bin, S, Chakraborty, N, Saleem, M, Ngonga Ngomo, AC & Jabeen, H 2017, Distributed semantic analytics using the SANSA stack. in M Fernandez, C d’Amato, V Tamma, P Cudre-Mauroux, F Lecue, C Lange, J Sequeda & J Heflin (Hrsg.), The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 10588 LNCS, Springer-Verlag Austria, S. 147-155, 16. Internationale Semantic-Web-Konferenz, ISWC 2017, Vienna, Österreich, 21.10.17. https://doi.org/10.1007/978-3-319-68204-4_15

Distributed semantic analytics using the SANSA stack. / Lehmann, Jens; Sejdiu, Gezim; Bühmann, Lorenz et al.
The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings. Hrsg. / Miriam Fernandez; Claudia d’Amato; Valentina Tamma; Philippe Cudre-Mauroux; Freddy Lecue; Christoph Lange; Juan Sequeda; Jeff Heflin. Springer-Verlag Austria, 2017. S. 147-155 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 10588 LNCS).

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

TY - CHAP

T1 - Distributed semantic analytics using the SANSA stack

AU - Lehmann, Jens

AU - Sejdiu, Gezim

AU - Bühmann, Lorenz

AU - Westphal, Patrick

AU - Stadler, Claus

AU - Ermilov, Ivan

AU - Bin, Simon

AU - Chakraborty, Nilesh

AU - Saleem, Muhammad

AU - Ngonga Ngomo, Axel Cyrille

AU - Jabeen, Hajira

N1 - Conference code: 16

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N2 - A major research challenge is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and reasoning. Analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases, and most analytics approaches which do scale horizontally (i.e., can be executed in a distributed environment) work on simple feature-vector-based input. This software framework paper describes the ongoing Semantic Analytics Stack (SANSA) project, which supports expressive and scalable semantic analytics by providing functionality for distributed computing on RDF data.

AB - A major research challenge is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and reasoning. Analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases, and most analytics approaches which do scale horizontally (i.e., can be executed in a distributed environment) work on simple feature-vector-based input. This software framework paper describes the ongoing Semantic Analytics Stack (SANSA) project, which supports expressive and scalable semantic analytics by providing functionality for distributed computing on RDF data.

KW - Informatics

UR - https://www.scopus.com/pages/publications/85032189321

U2 - 10.1007/978-3-319-68204-4_15

DO - 10.1007/978-3-319-68204-4_15

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AN - SCOPUS:85032189321

SN - 9783319682037

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 147

EP - 155

BT - The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings

A2 - Fernandez, Miriam

A2 - d’Amato, Claudia

A2 - Tamma, Valentina

A2 - Cudre-Mauroux, Philippe

A2 - Lecue, Freddy

A2 - Lange, Christoph

A2 - Sequeda, Juan

A2 - Heflin, Jeff

PB - Springer-Verlag Austria

T2 - 16th International Semantic Web Conference, ISWC 2017

Y2 - 21 October 2017 through 25 October 2017

ER -

Lehmann J, Sejdiu G, Bühmann L, Westphal P, Stadler C, Ermilov I et al. Distributed semantic analytics using the SANSA stack. in Fernandez M, d’Amato C, Tamma V, Cudre-Mauroux P, Lecue F, Lange C, Sequeda J, Heflin J, Hrsg., The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings. Springer-Verlag Austria. 2017. S. 147-155. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-68204-4_15

Distributed semantic analytics using the SANSA stack

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