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LODFlow: A workflow management system for linked data processing

 
: Rautenberg, S.; Ermilov, I.; Marx, E.; Auer, S.; Ngomo, A.-C.N.

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Association for Computing Machinery -ACM-:
11th International Conference on Semantic Systems, SEMANTiCS 2015. Proceedings : 16-17-September-2015, Vienna, Austria
New York: ACM, 2015
ISBN: 978-1-4503-3462-4
S.137-144
International Conference on Semantic Systems (SEMANTICS) <11, 2015, Vienna>
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

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.

: http://publica.fraunhofer.de/dokumente/N-418122.html