research-article

LODFlow: a workflow management system for linked data processing

Authors:

Sandro Rautenberg,

Axel-Cyrille N. NgomoAuthors Info & Claims

SEMANTICS '15: Proceedings of the 11th International Conference on Semantic Systems

Pages 137 - 144

https://doi.org/10.1145/2814864.2814882

Published: 16 September 2015 Publication History

Abstract

The extraction and maintenance of Linked Data datasets is a cumbersome, time-consuming and resource-intensive activity. The cost for producing Linked Data can be reduced by a workflow management system, which describes plans to systematically support the lifecycle of RDF datasets. We present the LODFlow Linked Data Workflow Management System, which provides an environment for planning, executing, reusing, and documenting Linked Data workflows. The LODFlow approach is based on a comprehensive knowledge model for describing the workflows and a workflow execution engine supporting systematic workflow execution, reporting, and exception handling. The environment was evaluated in a large-scale real-world use case. As result, LODFlow supports Linked Data engineers to systematically plan, execute and assess Linked Data production and maintenance workflows, thus improving efficiency, ease-of-use, reproducibility, reuseability and provenance.

The environment was evaluated in a large-scale real-world use case. As result, LODFlow supports Linked Data engineers to systematically plan, execute and assess Linked Data production and maintenance workflows, thus improving efficiency, ease-of-use, reproducibility, reuseability and provenance.

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Cited By

Taelman RVan Herwegen JVander Sande MVerborgh R(2022)Components.js: Semantic dependency injectionSemantic Web10.3233/SW-22294514:1(135-153)Online publication date: 30-Nov-2022
https://doi.org/10.3233/SW-222945
Silva Mde Faria Cordeiro KCavalcanti M(2021)Sec4ML: An approach to support Cybersecurity Data Publishing for Machine Learning tasks2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)10.1109/EDOCW52865.2021.00053(226-235)Online publication date: Oct-2021
https://doi.org/10.1109/EDOCW52865.2021.00053
Frank MZander S(2019)The Linked Data Wiki: Leveraging Organizational Knowledge Bases with Linked Open DataPrimate Life Histories, Sex Roles, and Adaptability10.1007/978-3-030-15640-4_15(294-319)Online publication date: 15-Mar-2019
https://doi.org/10.1007/978-3-030-15640-4_15
Show More Cited By

Index Terms

LODFlow: a workflow management system for linked data processing
1. Applied computing
  1. Enterprise computing
    1. Business process management
2. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management

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Published In

cover image ACM Other conferences

SEMANTICS '15: Proceedings of the 11th International Conference on Semantic Systems

September 2015

220 pages

ISBN:9781450334624

DOI:10.1145/2814864

Editors:
Sebastian Hellmann
AKSW/KILT, Universität Leipzig, Germany
,
Josiane Xavier Parreira
Siemens AG Austria, Austria
,
Axel Polleres
Vienna University of Economy and Business (WU), Austria

Copyright © 2015 ACM.

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 the author(s) 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: 16 September 2015

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Funding Sources

FP7 -- GeoKnow project
Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES/Brazil)
BMWi -- project SAKE

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SEMANTiCS '15

SEMANTiCS '15: 11th International Conference on Semantic Systems

September 16 - 17, 2015

Vienna, Austria

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SEMANTICS '15 Paper Acceptance Rate 22 of 97 submissions, 23%;

Overall Acceptance Rate 40 of 182 submissions, 22%

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Cited By

Taelman RVan Herwegen JVander Sande MVerborgh R(2022)Components.js: Semantic dependency injectionSemantic Web10.3233/SW-22294514:1(135-153)Online publication date: 30-Nov-2022
https://doi.org/10.3233/SW-222945
Silva Mde Faria Cordeiro KCavalcanti M(2021)Sec4ML: An approach to support Cybersecurity Data Publishing for Machine Learning tasks2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)10.1109/EDOCW52865.2021.00053(226-235)Online publication date: Oct-2021
https://doi.org/10.1109/EDOCW52865.2021.00053
Frank MZander S(2019)The Linked Data Wiki: Leveraging Organizational Knowledge Bases with Linked Open DataPrimate Life Histories, Sex Roles, and Adaptability10.1007/978-3-030-15640-4_15(294-319)Online publication date: 15-Mar-2019
https://doi.org/10.1007/978-3-030-15640-4_15
Knap THanečák PKlímek JMader CNečaský MVan Nuffelen BŠkoda P(2018)UnifiedViewsSemantic Web10.3233/SW-1802919:5(661-676)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.3233/SW-180291
Trinh TAryan PDo BEkaputra FKiesling ERauber AWetz PTjoa ASheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Linked data processing provenanceProceedings of the International Conference on Web Intelligence10.1145/3106426.3106495(88-96)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106495

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