Semantic Representation of Scientific Publications

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Sahar Vahdati
  • Said Fathalla
  • Sören Auer
  • Christoph Lange
  • Maria Esther Vidal

Organisationseinheiten

Externe Organisationen

  • Rheinische Friedrich-Wilhelms-Universität Bonn
  • Alexandria University
  • Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme (IAIS)
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksDigital Libraries for Open Knowledge
Untertitel23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings
Herausgeber/-innenAntoine Doucet, Antoine Isaac, Koraljka Golub, Trond Aalberg, Adam Jatowt
ErscheinungsortCham
Herausgeber (Verlag)Springer Verlag
Seiten375-379
Seitenumfang5
Auflage1.
ISBN (elektronisch)9783030307608
ISBN (Print)9783030307592
PublikationsstatusVeröffentlicht - 30 Aug. 2019
Veranstaltung23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019 - Oslo, Norwegen
Dauer: 9 Sept. 201912 Sept. 2019

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band11799 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Abstract

In this work, we tackle the problem of generating comprehensive overviews of research findings in a structured and comparable way. To bring structure to such information and thus to enable researchers to, e.g., explore domain overviews, we present an approach for automatic unveiling of realm overviews for research artifacts (Aurora), an approach to generate overviews of research domains and their relevant artifacts. Aurora is a semi-automatic crowd-sourcing workflow that captures such information into the OpenResearch.org semantic wiki. Our evaluation confirms that Aurora, when compared to the current manual approach, reduces the effort for researchers to compile and read survey papers.

ASJC Scopus Sachgebiete

Zitieren

Semantic Representation of Scientific Publications. / Vahdati, Sahar; Fathalla, Said; Auer, Sören et al.
Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings. Hrsg. / Antoine Doucet; Antoine Isaac; Koraljka Golub; Trond Aalberg; Adam Jatowt. 1. Aufl. Cham: Springer Verlag, 2019. S. 375-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 11799 LNCS).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Vahdati, S, Fathalla, S, Auer, S, Lange, C & Vidal, ME 2019, Semantic Representation of Scientific Publications. in A Doucet, A Isaac, K Golub, T Aalberg & A Jatowt (Hrsg.), Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings. 1. Aufl., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 11799 LNCS, Springer Verlag, Cham, S. 375-379, 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norwegen, 9 Sept. 2019. https://doi.org/10.1007/978-3-030-30760-8_37
Vahdati, S., Fathalla, S., Auer, S., Lange, C., & Vidal, M. E. (2019). Semantic Representation of Scientific Publications. In A. Doucet, A. Isaac, K. Golub, T. Aalberg, & A. Jatowt (Hrsg.), Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings (1. Aufl., S. 375-379). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 11799 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-30760-8_37
Vahdati S, Fathalla S, Auer S, Lange C, Vidal ME. Semantic Representation of Scientific Publications. in Doucet A, Isaac A, Golub K, Aalberg T, Jatowt A, Hrsg., Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings. 1. Aufl. Cham: Springer Verlag. 2019. S. 375-379. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-30760-8_37
Vahdati, Sahar ; Fathalla, Said ; Auer, Sören et al. / Semantic Representation of Scientific Publications. Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings. Hrsg. / Antoine Doucet ; Antoine Isaac ; Koraljka Golub ; Trond Aalberg ; Adam Jatowt. 1. Aufl. Cham : Springer Verlag, 2019. S. 375-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
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title = "Semantic Representation of Scientific Publications",
abstract = "In this work, we tackle the problem of generating comprehensive overviews of research findings in a structured and comparable way. To bring structure to such information and thus to enable researchers to, e.g., explore domain overviews, we present an approach for automatic unveiling of realm overviews for research artifacts (Aurora), an approach to generate overviews of research domains and their relevant artifacts. Aurora is a semi-automatic crowd-sourcing workflow that captures such information into the OpenResearch.org semantic wiki. Our evaluation confirms that Aurora, when compared to the current manual approach, reduces the effort for researchers to compile and read survey papers.",
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AU - Vahdati, Sahar

AU - Fathalla, Said

AU - Auer, Sören

AU - Lange, Christoph

AU - Vidal, Maria Esther

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N2 - In this work, we tackle the problem of generating comprehensive overviews of research findings in a structured and comparable way. To bring structure to such information and thus to enable researchers to, e.g., explore domain overviews, we present an approach for automatic unveiling of realm overviews for research artifacts (Aurora), an approach to generate overviews of research domains and their relevant artifacts. Aurora is a semi-automatic crowd-sourcing workflow that captures such information into the OpenResearch.org semantic wiki. Our evaluation confirms that Aurora, when compared to the current manual approach, reduces the effort for researchers to compile and read survey papers.

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KW - Metadata extraction

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A2 - Jatowt, Adam

PB - Springer Verlag

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