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

by Geleta, David , Payne, Terry R , Benedek Rozemberczki , Tamma, Valentina , Gogleva, Anna , Nikolov, Andriy , ODonoghue, Mark

in Graph theory / Hierarchies / Knowledge representation / Libraries / Nodes / Reproduction (copying)

2022

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

by Geleta, David , Payne, Terry R , Benedek Rozemberczki , Tamma, Valentina , Gogleva, Anna , Nikolov, Andriy , ODonoghue, Mark

in Graph theory / Hierarchies / Knowledge representation / Libraries / Nodes / Reproduction (copying)

2022

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Paper

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

Geleta, David,

Payne, Terry R,

Benedek Rozemberczki,

Tamma, Valentina,

Gogleva, Anna,

Nikolov, Andriy,

ODonoghue, Mark

2022

Overview

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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Publisher

Cornell University Library, arXiv.org

Subject

Graph theory

/ Hierarchies

/ Knowledge representation

/ Libraries

/ Nodes

/ Reproduction (copying)