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.
National Chung Hsing University, Taiwan, University of Bonn & Fraunhofer IAIS
www.cs.uni-bonn.de
Msc.
AKSW, Universität Leipzig
www.aksw.org
Edgard is a Linked Data Expert at eccenca GmbH and guest researcher at INFAI and HTWK with broad experience in software engineering, project management, and designing innovative solutions. His main topics of interest rely on Semantic Web and Natural Language Processing over large knowledge graphs with a focus on information retrieval and distributed data management.
Director
Leibniz Information Center for Science & Technology
https://www.tib.eu/en/
Following stations at the universities of Dresden, Ekaterinburg, Leipzig, Pennsylvania, Bonn and the Fraunhofer Society, Prof. Auer was appointed Professor of Data Science and Digital Libraries at Leibniz Universität Hannover and Director of the TIB in 2017.
