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<pre>
13th International Workshop on Scalable Semantic
   Web Knowledge Base Systems (SSWS 2020)




At the 19th International Semantic Web Conference (ISWC2020),
Athens, Greece November, 2020
                    SSWS 2020 PC Co-chairs’ Message


SSWS 2020 is the thirteenth edition of the successful Scalable Semantic Web Knowledge Base
Systems (SSWS) workshop series. The SSWS series is focused on addressing scalability issues with
respect to the development and deployment of knowledge base systems on the Semantic Web. This
13th workshop aimed at providing a forum for discussing application-oriented issues of Semantic
Technologies, with the focus on systems that turn large volumes of real-world data into actionable
knowledge at industry domains. This goal imposed significant scalability requirements on storage
and processing systems and demands for reliable workflows to curate and validate data from various
sources. By inviting contributions that integrate methods and results from research on RDF and
Property Graphs, this workshop brought together researchers and practitioners to share their ideas
regarding building and evaluating scalable knowledge base systems for the web.
   This year we received 6 submissions. Each paper was carefully evaluated by three workshop
Program Committee members. Based on these reviews, we accepted 5 papers for presentation.
   We sincerely thank the authors for all the submissions and are grateful for the excellent work
by the Program Committee members.




November 2020                                                                     Thorsten Liebig
                                                                                   Achille Fokoue
                                                                                          Zhe Wu




   Copyright c 2020 for the individual papers by the papers’ authors. This volume and its papers
are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).
Program Committee
Achille Fokoue                       Mariano Rodrı́guez-Muro
IBM Watson Research Center, USA      Google, USA

Boris Motik                          Adila A. Krisnadhi
University of Oxford, UK             Universitas Indonesia

Raghava Mutharaju                    Zhe Wu
Wright State University, Ohio, USA   eBay, USA

Thorsten Liebig                      Ralf Möller
derivo GmbH, Germany                 University of Luebeck, Germany

Kavitha Srinivas                     Bernado Cuenca Grau
IBM Watson Research Center, USA      University of Oxford, UK
                                                        Table of Contents


Optimizing Approximate Membership Metadata in Triple Pattern Fragments for Clients
and Servers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .    1
   Ruben Taelman, Joachim Van Herwegen, Miel Vander Sande, Ruben Verborgh
Revisiting RDF storage layouts for efficient query answering . . . . . . . . . . . . . . . . . . . . . . . . . . . . .                                      17
   Maxime Buron, François Goasdoué, Ioana Manolescu, Tayeb Merabti, Marie-Laure
   Mugnier

Community-Based RDF Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .                          33
  Fredah Banda, Boris Motik
Template Libraries for Industrial Asset Maintenance: A Methodology for Scalable and
Maintainable Ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .             49
  Daniel P. Lupp, Melinda Hodkiewicz, Martin G. Skjæveland

Using Semantic Technologies to Manage a Data Lake: Data Catalog, Provenance and
Access Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .      65
   Henrik Dibowski, Stefan Schmid, Yulia Svetashova, Cory Henson, Tuan Tran

</pre>