Trav-SHACL: Efficiently validating networks of SHACL constraints

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

Autoren

  • MA³nica Figuera
  • Philipp D. Rohde
  • Maria Esther Vidal

Organisationseinheiten

Externe Organisationen

  • Rheinische Friedrich-Wilhelms-Universität Bonn
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksThe Web Conference 2021
UntertitelProceedings of the World Wide Web Conference, WWW 2021
Seiten3337-3348
Seitenumfang12
ISBN (elektronisch)9781450383127
PublikationsstatusVeröffentlicht - 19 Apr. 2021
VeranstaltungWorld Wide Web Conference (WWW 2021) - Ljubljana, Slowenien
Dauer: 19 Apr. 202123 Apr. 2021
Konferenznummer: 30

Abstract

Knowledge graphs have emerged as expressive data structures for Web data. Knowledge graph potential and the demand for ecosystems to facilitate their creation, curation, and understanding, is testified in diverse domains, e.g., biomedicine. The Shapes Constraint Language (SHACL) is the W3C recommendation language for integrity constraints over RDF knowledge graphs. Enabling quality assements of knowledge graphs, SHACL is rapidly gaining attention in real-world scenarios. SHACL models integrity constraints as a network of shapes, where a shape contains the constraints to be fullfiled by the same entities. The validation of a SHACL shape schema can face the issue of tractability during validation. To facilitate full adoption, efficient computational methods are required. We present Trav-SHACL, a SHACL engine capable of planning the traversal and execution of a shape schema in a way that invalid entities are detected early and needless validations are minimized. Trav-SHACL reorders the shapes in a shape schema for efficient validation and rewrites target and constraint queries for fast detection of invalid entities. Trav-SHACL is empirically evaluated on 27 testbeds executed against knowledge graphs of up to 34M triples. Our experimental results suggest that Trav-SHACL exhibits high performance gradually and reduces validation time by a factor of up to 28.93 compared to the state of the art.

ASJC Scopus Sachgebiete

Zitieren

Trav-SHACL: Efficiently validating networks of SHACL constraints. / Figuera, MA³nica; Rohde, Philipp D.; Vidal, Maria Esther.
The Web Conference 2021: Proceedings of the World Wide Web Conference, WWW 2021. 2021. S. 3337-3348.

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

Figuera, MA, Rohde, PD & Vidal, ME 2021, Trav-SHACL: Efficiently validating networks of SHACL constraints. in The Web Conference 2021: Proceedings of the World Wide Web Conference, WWW 2021. S. 3337-3348, World Wide Web Conference (WWW 2021), Ljubljana, Slowenien, 19 Apr. 2021. https://doi.org/10.1145/3442381.3449877
Figuera, MA., Rohde, P. D., & Vidal, M. E. (2021). Trav-SHACL: Efficiently validating networks of SHACL constraints. In The Web Conference 2021: Proceedings of the World Wide Web Conference, WWW 2021 (S. 3337-3348) https://doi.org/10.1145/3442381.3449877
Figuera MA, Rohde PD, Vidal ME. Trav-SHACL: Efficiently validating networks of SHACL constraints. in The Web Conference 2021: Proceedings of the World Wide Web Conference, WWW 2021. 2021. S. 3337-3348 doi: 10.1145/3442381.3449877
Figuera, MA³nica ; Rohde, Philipp D. ; Vidal, Maria Esther. / Trav-SHACL : Efficiently validating networks of SHACL constraints. The Web Conference 2021: Proceedings of the World Wide Web Conference, WWW 2021. 2021. S. 3337-3348
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Download

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AU - Figuera, MA³nica

AU - Rohde, Philipp D.

AU - Vidal, Maria Esther

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