A method for extending ontologies with application to the materials science domain

被引：1
作者：
Li H. [1 ,3 ]
Armiento R. [2 ,3 ]
Lambrix P. [1 ,3 ]
机构：
[1] Department of Computer and Information Science, Linköping University, Linköping
[2] Department of Physics, Chemistry and Biology, Linköping University, Linköping
[3] The Swedish e-Science Research Centre, Linköping University, Linköping
来源：
Data Science Journal | 2019年 / 18卷 / 01期
关键词：
Formal topical concept analysis; Materials science; Nanoparticle; Nanotechnology; Ontology; Topic model;
D O I：
10.5334/dsj-2019-050
中图分类号：
学科分类号：
摘要：
In the materials science domain the data-driven science paradigm has become the focus since the beginning of the 2000s. A large number of research groups and communities are building and developing data-driven workflows. However, much of the data and knowledge is stored in different heterogeneous data sources maintained by different groups. This leads to a reduced availability of the data and poor interoperability between systems in this domain. Ontology-based techniques are an important way to reduce these problems and a number of efforts have started. In this paper we investigate efforts in the materials science, and in particular in the nanotechnology domain, and show how such ontologies developed by domain experts, can be improved. We use a phrase-based topic model approach and formal topical concept analysis on unstructured text in this domain to suggest additional concepts and axioms for the ontology that should be validated by a domain expert. We describe the techniques and show the usefulness of the approach through an experiment where we extend two nanotechnology ontologies using approximately 600 titles and abstracts. © 2019 The Author(s).
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