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A Method for Extending Ontologies with Application to the Materials Science Domain
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-1881-3969
Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5571-0814
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. (IDA/ADIT)ORCID iD: 0000-0002-9084-0470
2019 (English)In: Data Science Journal, ISSN 1683-1470, E-ISSN 1683-1470, Vol. 18, no 1, p. 1-21, article id 50Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Ubiquity Press, 2019. Vol. 18, no 1, p. 1-21, article id 50
Keywords [en]
Ontology, Materials Science, Nanotechnology, Nanoparticle, Topic Model, Formal Topical Concept Analysis
National Category
Computer Sciences Materials Engineering
Identifiers
URN: urn:nbn:se:liu:diva-160711DOI: 10.5334/dsj-2019-050OAI: oai:DiVA.org:liu-160711DiVA, id: diva2:1357454
Funder
Swedish e‐Science Research CenterSwedish Research Council, 2018-04147CUGS (National Graduate School in Computer Science)Available from: 2019-10-03 Created: 2019-10-03 Last updated: 2019-12-03Bibliographically approved

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Armiento, Rickard

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