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.
%0 Conference Paper
%1 rautenberg-2015
%A Rautenberg, Sandro
%A Ermilov, Ivan
%A Marx, Edgard
%A Auer, Sören
%A Ngomo Ngonga, Axel-Cyrille
%B SEMANTiCS 2015
%D 2015
%K 2015 SIMBA auer geoknow group_aksw iermilov marx ngonga rautenberg sake simba
%T LODFlow -- a Workflow Management System for Linked Data Processing
%U http://svn.aksw.org/papers/2015/SEMANTICS_LDWPO/public.pdf
%X 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.
@inproceedings{rautenberg-2015,
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.},
added-at = {2024-03-04T14:14:54.000+0100},
author = {Rautenberg, Sandro and Ermilov, Ivan and Marx, Edgard and Auer, S\"oren and {Ngomo Ngonga}, Axel-Cyrille},
bdsk-url-1 = {http://svn.aksw.org/papers/2015/SEMANTICS_LDWPO/public.pdf},
biburl = {https://www.bibsonomy.org/bibtex/25d79dc4d9057afeb250fd35684560ff0/aksw},
booktitle = {SEMANTiCS 2015},
interhash = {2d0ef205de058284b2f62e8ef0127a82},
intrahash = {5d79dc4d9057afeb250fd35684560ff0},
keywords = {2015 SIMBA auer geoknow group_aksw iermilov marx ngonga rautenberg sake simba},
owner = {ivan},
timestamp = {2024-03-04T14:14:54.000+0100},
title = {LODFlow -- a Workflow Management System for Linked Data Processing},
url = {http://svn.aksw.org/papers/2015/SEMANTICS_LDWPO/public.pdf},
year = 2015
}