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Parallel RDF generation from heterogeneous big data

Authors:

Anastasia DimouAuthors Info & Claims

SBD '19: Proceedings of the International Workshop on Semantic Big Data

Article No.: 1, Pages 1 - 6

https://doi.org/10.1145/3323878.3325802

Published: 05 July 2019 Publication History

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Abstract

To unlock the value of increasingly available data in high volumes, we need flexible ways to integrate data across different sources. While semantic integration can be provided through RDF generation, current generators insufficiently scale in terms of volume. Generators are limited by memory constraints. Therefore, we developed the RMLStreamer, a generator that parallelizes the ingestion and mapping tasks of RDF generation across multiple instances. In this paper, we analyze what aspects are parallelizable and we introduce an approach for parallel RDF generation. We describe how we implemented our proposed approach, in the frame of the RMLStreamer, and how the resulting scaling behavior compares to other RDF generators. The RMLStreamer ingests data at 50% faster rate than existing generators through parallel ingestion.

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Cited By

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Sowiński PSzmeja PGanzha MPaprzycki M(2024)RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and PracticeElectronics10.3390/electronics1313255813:13(2558)Online publication date: 29-Jun-2024
https://doi.org/10.3390/electronics13132558
Cimmino AGarcía-Castro R(2024)Helio: A framework for implementing the life cycle of knowledge graphsSemantic Web10.3233/SW-23322415:1(223-249)Online publication date: 12-Jan-2024
https://doi.org/10.3233/SW-233224
Arenas-Guerrero JChaves-Fraga DToledo JPérez MCorcho O(2024)Morph-KGC: Scalable knowledge graph materialization with mapping partitionsSemantic Web10.3233/SW-22313515:1(1-20)Online publication date: 12-Jan-2024
https://doi.org/10.3233/SW-223135
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Index Terms

Parallel RDF generation from heterogeneous big data
1. Information systems
  1. World Wide Web
    1. Web data description languages
      1. Semantic web description languages

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Information & Contributors

Information

Published In

SBD '19: Proceedings of the International Workshop on Semantic Big Data

July 2019

57 pages

ISBN:9781450367660

DOI:10.1145/3323878

Editors:
Sven Groppe
University of Lübeck, Germany
,
Le Gruenwald
University of Oklahoma

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 July 2019

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Research-article

Funding Sources

Flanders Innovation & Entrepreneurship (VLAIO)
Ghent University
imec
European Union

Conference

SIGMOD/PODS '19

Sponsor:

SIGMOD

SIGMOD/PODS '19: International Conference on Management of Data

July 5, 2019

Amsterdam, Netherlands

Acceptance Rates

SBD '19 Paper Acceptance Rate 8 of 15 submissions, 53%;

Overall Acceptance Rate 30 of 54 submissions, 56%

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Cited By

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Sowiński PSzmeja PGanzha MPaprzycki M(2024)RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and PracticeElectronics10.3390/electronics1313255813:13(2558)Online publication date: 29-Jun-2024
https://doi.org/10.3390/electronics13132558
Cimmino AGarcía-Castro R(2024)Helio: A framework for implementing the life cycle of knowledge graphsSemantic Web10.3233/SW-23322415:1(223-249)Online publication date: 12-Jan-2024
https://doi.org/10.3233/SW-233224
Arenas-Guerrero JChaves-Fraga DToledo JPérez MCorcho O(2024)Morph-KGC: Scalable knowledge graph materialization with mapping partitionsSemantic Web10.3233/SW-22313515:1(1-20)Online publication date: 12-Jan-2024
https://doi.org/10.3233/SW-223135
De Brouwer MBonte PArndt DVander Sande MDimou AVerborgh RDe Turck FOngenae F(2024)Optimized continuous homecare provisioning through distributed data-driven semantic services and cross-organizational workflowsJournal of Biomedical Semantics10.1186/s13326-024-00303-415:1Online publication date: 6-Jun-2024
https://doi.org/10.1186/s13326-024-00303-4
Flores JRabbani KNadal SGómez CRomero OJamin EDasiopoulou S(2023)Incremental schema integration for data wrangling via knowledge graphsSemantic Web10.3233/SW-233347(1-38)Online publication date: 8-Jun-2023
https://doi.org/10.3233/SW-233347
Bonte PTommasini R(2023)Streaming linked data: A survey on life cycle complianceJournal of Web Semantics10.1016/j.websem.2023.10078577(100785)Online publication date: Jul-2023
https://doi.org/10.1016/j.websem.2023.100785
Van Assche DDelva THaesendonck GHeyvaert PDe Meester BDimou A(2023)Declarative RDF graph generation from heterogeneous (semi-)structured dataWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2022.10075375:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.websem.2022.100753
Wang SYan JLiu YHu PCai HJiang L(2023)Parallel Construction of Knowledge Graphs from Relational DatabasesPRICAI 2023: Trends in Artificial Intelligence10.1007/978-981-99-7019-3_42(467-479)Online publication date: 10-Nov-2023
https://doi.org/10.1007/978-981-99-7019-3_42
Oo S(2023)A Window into the Multiple Views of Linked DataThe Semantic Web: ESWC 2023 Satellite Events10.1007/978-3-031-43458-7_51(331-340)Online publication date: 21-Oct-2023
https://doi.org/10.1007/978-3-031-43458-7_51
Wardani DMarshallia MWijayanto ASetyadi H(2022)Semi-Automatic Generating Semantic Markup Webpage from Structured Data with Semantic Matching2022 14th International Conference on Information Technology and Electrical Engineering (ICITEE)10.1109/ICITEE56407.2022.9954103(85-90)Online publication date: 18-Oct-2022
https://doi.org/10.1109/ICITEE56407.2022.9954103
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