Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG

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

Autoren

  • Fajar J. Ekaputra
  • Majlinda Llugiqi
  • Marta Sabou
  • Andreas Ekelhart
  • Heiko Paulheim
  • Anna Breit
  • Artem Revenko
  • Laura Waltersdorfer
  • Kheir Eddine Farfar
  • Sören Auer

Organisationseinheiten

Externe Organisationen

  • Wirtschaftsuniversität Wien
  • Technische Universität Wien (TUW)
  • Universität Wien
  • SBA Research
  • Universität Mannheim
  • Semantic Web Company (SWC)
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksThe Semantic Web
Untertitel20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings
Herausgeber/-innenCatia Pesquita, Daniel Faria, Ernesto Jimenez-Ruiz, Jamie McCusker, Mauro Dragoni, Anastasia Dimou, Raphael Troncy, Sven Hertling
ErscheinungsortCham
Herausgeber (Verlag)Springer Science and Business Media Deutschland GmbH
Seiten372-389
Seitenumfang18
ISBN (elektronisch)978-3-031-33455-9
ISBN (Print)9783031334542
PublikationsstatusVeröffentlicht - 2023
Veranstaltung20th International Conference on The Semantic Web, ESWC 2023 - Hersonissos, Griechenland
Dauer: 28 Mai 20231 Juni 2023

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band13870 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Abstract

The overall AI trend of creating neuro-symbolic systems is reflected in the Semantic Web community with an increased interest in the development of systems that rely on both Semantic Web resources and Machine Learning components (SWeMLS, for short). However, understanding trends and best practices in this rapidly growing field is hampered by a lack of standardized descriptions of these systems and an annotated corpus of such systems. To address these gaps, we leverage the results of a large-scale systematic mapping study collecting information about 470 SWeMLS papers and formalize these into one resource containing: (i) the SWeMLS ontology, (ii) the SWeMLS pattern library containing machine-actionable descriptions of 45 frequently occurring SWeMLS workflows, and (iii) SWEMLS-KG, a knowledge graph including machine-actionable metadata of the papers in terms of the SWeMLS ontology. This resource provides the first framework for semantically describing and organizing SWeMLS thus making a key impact in (1) understanding the status quo of the field based on the published paper corpus and (2) enticing the uptake of machine-processable system documentation in the SWeMLS area.

ASJC Scopus Sachgebiete

Zitieren

Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. / Ekaputra, Fajar J.; Llugiqi, Majlinda; Sabou, Marta et al.
The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings. Hrsg. / Catia Pesquita; Daniel Faria; Ernesto Jimenez-Ruiz; Jamie McCusker; Mauro Dragoni; Anastasia Dimou; Raphael Troncy; Sven Hertling. Cham: Springer Science and Business Media Deutschland GmbH, 2023. S. 372-389 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13870 LNCS).

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

Ekaputra, FJ, Llugiqi, M, Sabou, M, Ekelhart, A, Paulheim, H, Breit, A, Revenko, A, Waltersdorfer, L, Farfar, KE & Auer, S 2023, Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. in C Pesquita, D Faria, E Jimenez-Ruiz, J McCusker, M Dragoni, A Dimou, R Troncy & S Hertling (Hrsg.), The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 13870 LNCS, Springer Science and Business Media Deutschland GmbH, Cham, S. 372-389, 20th International Conference on The Semantic Web, ESWC 2023, Hersonissos, Griechenland, 28 Mai 2023. https://doi.org/10.48550/arXiv.2303.15113, https://doi.org/10.1007/978-3-031-33455-9_22
Ekaputra, F. J., Llugiqi, M., Sabou, M., Ekelhart, A., Paulheim, H., Breit, A., Revenko, A., Waltersdorfer, L., Farfar, K. E., & Auer, S. (2023). Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. In C. Pesquita, D. Faria, E. Jimenez-Ruiz, J. McCusker, M. Dragoni, A. Dimou, R. Troncy, & S. Hertling (Hrsg.), The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings (S. 372-389). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13870 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.48550/arXiv.2303.15113, https://doi.org/10.1007/978-3-031-33455-9_22
Ekaputra FJ, Llugiqi M, Sabou M, Ekelhart A, Paulheim H, Breit A et al. Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. in Pesquita C, Faria D, Jimenez-Ruiz E, McCusker J, Dragoni M, Dimou A, Troncy R, Hertling S, Hrsg., The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings. Cham: Springer Science and Business Media Deutschland GmbH. 2023. S. 372-389. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2023 Mai 22. doi: 10.48550/arXiv.2303.15113, 10.1007/978-3-031-33455-9_22
Ekaputra, Fajar J. ; Llugiqi, Majlinda ; Sabou, Marta et al. / Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings. Hrsg. / Catia Pesquita ; Daniel Faria ; Ernesto Jimenez-Ruiz ; Jamie McCusker ; Mauro Dragoni ; Anastasia Dimou ; Raphael Troncy ; Sven Hertling. Cham : Springer Science and Business Media Deutschland GmbH, 2023. S. 372-389 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
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title = "Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG",
abstract = "The overall AI trend of creating neuro-symbolic systems is reflected in the Semantic Web community with an increased interest in the development of systems that rely on both Semantic Web resources and Machine Learning components (SWeMLS, for short). However, understanding trends and best practices in this rapidly growing field is hampered by a lack of standardized descriptions of these systems and an annotated corpus of such systems. To address these gaps, we leverage the results of a large-scale systematic mapping study collecting information about 470 SWeMLS papers and formalize these into one resource containing: (i) the SWeMLS ontology, (ii) the SWeMLS pattern library containing machine-actionable descriptions of 45 frequently occurring SWeMLS workflows, and (iii) SWEMLS-KG, a knowledge graph including machine-actionable metadata of the papers in terms of the SWeMLS ontology. This resource provides the first framework for semantically describing and organizing SWeMLS thus making a key impact in (1) understanding the status quo of the field based on the published paper corpus and (2) enticing the uptake of machine-processable system documentation in the SWeMLS area.",
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author = "Ekaputra, {Fajar J.} and Majlinda Llugiqi and Marta Sabou and Andreas Ekelhart and Heiko Paulheim and Anna Breit and Artem Revenko and Laura Waltersdorfer and Farfar, {Kheir Eddine} and S{\"o}ren Auer",
note = "Funding Information: This work has been supported by the Austrian Science Fund (FWF) under grant V0745 (HOnEst) and FFG Project OBARIS (Grant Agreement No 877389). SBA Research (SBA-K1) is a COMET Center within the COMET-Competence Centers for Excellent Technologies Programme and funded by BMK, BMAW, and the federal state of Vienna. The COMET Programme is managed by FFG. Moreover, financial support by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, DFG NFDI4DataScience (No. 460234259) and ERC ScienceGRAPH (GA ID: 819536) is gratefully acknowledged. ; 20th International Conference on The Semantic Web, ESWC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",
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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
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booktitle = "The Semantic Web",
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Download

TY - GEN

T1 - Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG

AU - Ekaputra, Fajar J.

AU - Llugiqi, Majlinda

AU - Sabou, Marta

AU - Ekelhart, Andreas

AU - Paulheim, Heiko

AU - Breit, Anna

AU - Revenko, Artem

AU - Waltersdorfer, Laura

AU - Farfar, Kheir Eddine

AU - Auer, Sören

N1 - Funding Information: This work has been supported by the Austrian Science Fund (FWF) under grant V0745 (HOnEst) and FFG Project OBARIS (Grant Agreement No 877389). SBA Research (SBA-K1) is a COMET Center within the COMET-Competence Centers for Excellent Technologies Programme and funded by BMK, BMAW, and the federal state of Vienna. The COMET Programme is managed by FFG. Moreover, financial support by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, DFG NFDI4DataScience (No. 460234259) and ERC ScienceGRAPH (GA ID: 819536) is gratefully acknowledged.

PY - 2023

Y1 - 2023

N2 - The overall AI trend of creating neuro-symbolic systems is reflected in the Semantic Web community with an increased interest in the development of systems that rely on both Semantic Web resources and Machine Learning components (SWeMLS, for short). However, understanding trends and best practices in this rapidly growing field is hampered by a lack of standardized descriptions of these systems and an annotated corpus of such systems. To address these gaps, we leverage the results of a large-scale systematic mapping study collecting information about 470 SWeMLS papers and formalize these into one resource containing: (i) the SWeMLS ontology, (ii) the SWeMLS pattern library containing machine-actionable descriptions of 45 frequently occurring SWeMLS workflows, and (iii) SWEMLS-KG, a knowledge graph including machine-actionable metadata of the papers in terms of the SWeMLS ontology. This resource provides the first framework for semantically describing and organizing SWeMLS thus making a key impact in (1) understanding the status quo of the field based on the published paper corpus and (2) enticing the uptake of machine-processable system documentation in the SWeMLS area.

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A2 - Troncy, Raphael

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