OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes

• URL: http://arxiv.org/abs/2206.02238v1
• Date: Sun, 5 Jun 2022 18:52:26 GMT
• Title: OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes
• Authors: David Geleta, Andriy Nikolov, Mark ODonoghue, Benedek Rozemberczki, Anna Gogleva, Valentina Tamma, Terry R. Payne
• Abstract summary: OntoMerger is a Python integration library whose functionality is to deduplicate KG nodes. Our approach takes a set of KG nodes, mappings and disconnected and generates a set of merged nodes together with a connected hierarchy. OntoMerger can be applied to a wide variety of KGs.
• Score: 2.6553713413568913
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Duplication of nodes is a common problem encountered when building knowledge graphs (KGs) from heterogeneous datasets, where it is crucial to be able to merge nodes having the same meaning. OntoMerger is a Python ontology integration library whose functionality is to deduplicate KG nodes. Our approach takes a set of KG nodes, mappings and disconnected hierarchies and generates a set of merged nodes together with a connected hierarchy. In addition, the library provides analytic and data testing functionalities that can be used to fine-tune the inputs, further reducing duplication, and to increase connectivity of the output graph. OntoMerger can be applied to a wide variety of ontologies and KGs. In this paper we introduce OntoMerger and illustrate its functionality on a real-world biomedical KG.

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