Implementation-independent Knowledge Graph Construction Workflows using FnO CompositionDownload PDF

11 Mar 2022, 23:09 (modified: 12 Mar 2022, 14:21)KGCW 2022Readers: Everyone
Keywords: Workflows, Interoperability, Reproducibility, Function Composition
TL;DR: Describing workflows through the composition of implementation-independent semantic function descriptions.
Abstract: Knowledge Graph construction is typically a task within larger workflows, with a tight coupling between the abstract workflow and its execution. Mapping languages increase interoperability and reproducibility of the mapping process, however, this should be extended over the entire Knowledge Graph construction workflow. In this paper, we introduce an interoperable and reproducible solution for defining Knowledge Graph construction workflows leveraging Semantic Web technologies. We describe how a data flow workflow can be described interoperable (i.e., independent from the underlying technology stack) and reproducible (i.e., with detailed provenance) by composing semantic abstract function descriptions; and how such a semantic workflow can be automatically executed across technology stacks. We demonstrate that composing functions using the Function Ontology allows for functional descriptions of entire workflows, automatically executable using a Function Ontology Handler implementation. The semantic descriptions allow for interoperable workflows, the alignment with P-PLAN and PROV-O allows for reproducibility, and the mapping to concrete implementations allows for automatic execution.
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