Abstract
Knowledge graphs can be used to help scientists integrate and explore their data in novel ways. NanoMine, built with the Whyis knowledge graph framework, integrates diverse data from over 1,700 polymer nanocomposite experiments. Polymer nanocomposites (polymer materials with nanometer-scale particles embedded in them) exhibit complex changes in their properties depending upon their composition or processing methods. Building an overall theory of how nanoparticles interact with the polymer they are embedded in therefore typically has to rely on an integrated view across hundreds of datasets. Because the NanoMine knowledge graph is able to integrate across many experiments, materials scientists can explore custom visualizations and, with minimal semantic training, produce custom visualizations of their own. NanoMine provides access to experimental results and their provenance in a linked data format that conforms to well-used semantic web ontologies and vocabularies (PROV-O, Schema.org, and the Semanticscience Integrated Ontology). We curated data described by an XML schema into an extensible knowledge graph format that enables users to more easily browse, filter, and visualize nanocomposite materials data. We evaluated NanoMine on the ability for material scientists to produce visualizations that help them explore and understand nanomaterials and assess the diversity of the integrated data. Additionally, NanoMine has been used by the materials science community to produce an integrated view of a journal special issue focusing on data sharing, demonstrating the advantages of sharing data in an interoperable manner.
Supported by the National Science Foundation.
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Available from the main NanoMine page at http://nanomine.org.
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McCusker, J.P., Keshan, N., Rashid, S., Deagen, M., Brinson, C., McGuinness, D.L. (2020). NanoMine: A Knowledge Graph for Nanocomposite Materials Science. In: Pan, J.Z., et al. The Semantic Web – ISWC 2020. ISWC 2020. Lecture Notes in Computer Science(), vol 12507. Springer, Cham. https://doi.org/10.1007/978-3-030-62466-8_10
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