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International Semantic Web Conference

ISWC 2020: The Semantic Web – ISWC 2020 pp 144–159Cite as

NanoMine: A Knowledge Graph for Nanocomposite Materials Science

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12507)

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.

Keywords

  • Knowledge graph
  • Semantic science
  • Knowledge representation

Supported by the National Science Foundation.

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Fig. 1.

Adapted from [3].

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Notes

  1. 1.

    https://automeris.io/WebPlotDigitizer/.

  2. 2.

    https://materialsmine.org/nm#/XMLCONV.

  3. 3.

    Available from the main NanoMine page at http://nanomine.org.

  4. 4.

    https://pppdb.uchicago.edu.

References

  1. Brinson, L.C., et al.: Polymer nanocomposite data: curation, frameworks, access, and potential for discovery and design. ACS Macro Lett. 9, 1086–1094 (2020)

    CrossRef  Google Scholar 

  2. Duerr, R.E., et al.: Formalizing the semantics of sea ice. Earth Sci. Inf. 8(1), 51–62 (2014). https://doi.org/10.1007/s12145-014-0177-z

    CrossRef  Google Scholar 

  3. Dumontier, M., et al.: The semantic science integrated ontology (SIO) for biomedical research and knowledge discovery. J. Biomed. Semant. 5(1), 14 (2014)

    CrossRef  Google Scholar 

  4. Ellis, B., Smith, R.: Polymers: A Property Database. CRC Press (2008)

    Google Scholar 

  5. Groth, P., Gibson, A., Velterop, J.: The anatomy of a nanopublication. Inf. Serv. Use 30(1–2), 51–56 (2010)

    Google Scholar 

  6. Koho, M., Heino, E., Hyvönen, E., et al.: SPARQL faceter-client-side faceted search based on SPARQL. In: LIME/SemDev@ ESWC (2016)

    Google Scholar 

  7. Lebo, T., Sahoo, S., McGuinness, D.: PROV-O: The PROV Ontology (2013). http://www.w3.org/TR/prov-o/

  8. McCusker, J.P., Chastain, K., Rashid, S., Norris, S., McGuinness, D.L.: SETLr: the semantic extract, transform, and load-r. PeerJ Preprints 6, e26476v1 (2018)

    Google Scholar 

  9. McCusker, J.P., Dumontier, M., Yan, R., He, S., Dordick, J.S., McGuinness, D.L.: Finding melanoma drugs through a probabilistic knowledge graph. PeerJ Comput. Sci. 3, e106 (2017)

    CrossRef  Google Scholar 

  10. McCusker, J.P., et al.: Broad, interdisciplinary science in tela: an exposure and child health ontology. In: Proceedings of the 2017 ACM on Web Science Conference, pp. 349–357 (2017)

    Google Scholar 

  11. Mrdjenovich, D., et al.: Propnet: a knowledge graph for materials science. Matter 2(2), 464–480 (2020). https://doi.org/10.1016/j.matt.2019.11.013

    CrossRef  Google Scholar 

  12. Otsuka, S., Kuwajima, I., Hosoya, J., Xu, Y., Yamazaki, M.: Polyinfo: polymer database for polymeric materials design. In: 2011 International Conference on Emerging Intelligent Data and Web Technologies, pp. 22–29. IEEE (2011)

    Google Scholar 

  13. Piñero, J., et al.: Disgenet: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. gkw943 (2016)

    Google Scholar 

  14. Satyanarayan, A., Moritz, D., Wongsuphasawat, K., Heer, J.: Vega-lite: a grammar of interactive graphics. IEEE Trans. Vis. Comput. Graph. 23(1), 341–350 (2016)

    CrossRef  Google Scholar 

  15. Schadler, L., Brinson, L.C., Sawyer, W.: Polymer nanocomposites: a small part of the story. JOM 59(3), 53–60 (2007)

    CrossRef  Google Scholar 

  16. Strötgen, J., et al.: Towards the bosch materials science knowledge base. In: ISWC Satellites (2019)

    Google Scholar 

  17. Zhang, X., Liu, X., Li, X., Pan, D.: MMKG: an approach to generate metallic materials knowledge graph based on DBpedia and Wikipedia. Comput. Phys. Commun. 211, 98–112 (2017). https://doi.org/10.1016/j.cpc.2016.07.005. High Performance Computing for Advanced Modeling and Simulation of Materials

  18. Zhao, H., et al.: Nanomine schema: an extensible data representation for polymer nanocomposites. APL Mater. 6(11), 111108 (2018)

    CrossRef  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, USA

    James P. McCusker, Neha Keshan, Sabbir Rashid & Deborah L. McGuinness

  2. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA

    Cate Brinson

  3. College of Engineering and Mathematical Sciences, University of Vermont, Burlington, VT, USA

    Michael Deagen

Authors
  1. James P. McCusker
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  2. Neha Keshan
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  3. Sabbir Rashid
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  4. Michael Deagen
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  5. Cate Brinson
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  6. Deborah L. McGuinness
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Corresponding author

Correspondence to James P. McCusker .

Editor information

Editors and Affiliations

  1. University of Edinburgh, Edinburgh, UK

    Jeff Z. Pan

  2. University of Liverpool, Liverpool, UK

    Valentina Tamma

  3. University of Bari, Bari, Italy

    Claudia d’Amato

  4. University of California, Santa Barbara, Santa Barbara, CA, USA

    Krzysztof Janowicz

  5. California State University, Long Beach, Long Beach, CA, USA

    Bo Fu

  6. Vienna University of Economics and Business, Vienna, Austria

    Axel Polleres

  7. Rensselaer Polytechnic Institute, Troy, NY, USA

    Oshani Seneviratne

  8. Massachusetts Institute of Technology, Cambridge, MA, USA

    Lalana Kagal

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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: , 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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  • DOI: https://doi.org/10.1007/978-3-030-62466-8_10

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