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International Conference on Data Analytics and Management in Data Intensive Domains

DAMDID/RCDL 2019: Data Analytics and Management in Data Intensive Domains pp 82–93Cite as

Applied Ontologies for Managing Graphic Resources in Quantitative Spectroscopy

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1223))

Abstract

The report presents the tasks on graphical resources management thoroughly describing applied ontologies of GrafOnto research graphics collection used for solving problems of spectroscopy. Two groups of the tasks on graphical resources management are discussed in the paper. The first group is oriented on the quality analysis of graphical resources and the representation of these results as a graphical resources ontology. The second group of tasks is associated with the automatic class creation for the aforementioned ontology. The problems of ontology modularity and automatic classes’ generation are being discussed. Examples of solving reduction problem as well as applied ontologies metrics are presented.

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Acknowledgements

The authors are grateful to Profs. I.V. Ptashnik and N.N. Filippov for providing original data pertaining to figures in their publications. The work was supported by the Basic Research Program no. AAAA-A17-117021310148-7.

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Authors and Affiliations

  1. Institute of Atmospheric Optics, SB RAS, Tomsk, 634055, Russia

    Nikolai Lavrentev, Alexei Privezentsev & Alexander Fazliev

Authors
  1. Nikolai Lavrentev
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  2. Alexei Privezentsev
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  3. Alexander Fazliev
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Corresponding author

Correspondence to Alexander Fazliev .

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Editors and Affiliations

  1. Kazan Federal University, Kazan, Russia

    Alexander Elizarov

  2. National Research University Higher School of Economics, St. Petersburg, Russia

    Boris Novikov

  3. Federal Research Center “Computer Science and Control”, Moscow, Russia

    Sergey Stupnikov

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Lavrentev, N., Privezentsev, A., Fazliev, A. (2020). Applied Ontologies for Managing Graphic Resources in Quantitative Spectroscopy. In: Elizarov, A., Novikov, B., Stupnikov, S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2019. Communications in Computer and Information Science, vol 1223. Springer, Cham. https://doi.org/10.1007/978-3-030-51913-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-51913-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51912-4

  • Online ISBN: 978-3-030-51913-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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