LDWPO: the Linked Data Workflow Project ontology

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Maintaining Linked Data datasets is a time-consuming and resource-intensive activity. The cost for maintaining Linked Data can, however, be reduced by using a workflow framework, which provides methods to systematically support the lifecycle of RDF datasets. We present the main component of such a framework, an ontology for orchestrating Linked Data processing workflows dubbed the Linked Data Workflow Project ontology. We introduce the Plan, Method, and Execution classes, which allow describing important maintenance tasks. We show that our ontology facilitates the description of the complete production workflow for RDF datasets, the explication of the methods and tools utilized in such a workflow and the execution of these workflows in a (semi-)automatized fashion. Hence, our approach enables the reproducibility and repeatability of Linked Data processing steps.

Project Team

News

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We are happy to announce that we are partnering again with the SEMANTiCS Conference which will host this year’s DBpedia Day on September 13, 2022. Read more about "DBpedia Day @ SEMANTiCS 2022"

DBpedia Knowledge Engineering PhD Symposium ( 2022-05-02T16:59:37+02:00 by Julia Holze)

2022-05-02T16:59:37+02:00 by Julia Holze

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Tutorial @ Knowledge Graph Conference 2022 ( 2022-04-25T12:24:06+02:00 by Julia Holze)

2022-04-25T12:24:06+02:00 by Julia Holze

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International Workshop on Data-driven Resilience Research 2022 ( 2022-04-21T14:43:27+02:00 by Julia Holze)

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DBpedia @ Google Summer of Code Program 2022 ( 2022-03-23T14:26:48+01:00 by Julia Holze)

2022-03-23T14:26:48+01:00 by Julia Holze

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