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Managing Data-Intensive Research Problem-Solving Lifecycle

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Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1427))

Abstract

Problem-solving lifecycle providing provable semantic interoperability and correct reuse of data, metadata, domain knowledge, methods, and processes on different levels of consideration is proposed. It includes ontological search, data model integration, schema mapping, entity resolution, method and process reuse, hypothesis testing, and data publishing. Problems are solved according to formal domain knowledge specifications over multiple integrated resources. The semantics of every decision may be formally verified.

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Acknowledgments

The research was carried out using the infrastructure of shared research facilities CKP “Informatics” of FRC CSC RAS [18], supported by the Russian Foundation for Basic Research (grants 19-07-01198, 18–29-22096, 18-07-01434).

Author information

Authors and Affiliations

  1. Institute of Informatics Problems, Federal Research Center “Computer Science and Control”, Russian Academy of Sciences, Moscow, Russia

    Nikolay Skvortsov & Sergey Stupnikov

Authors
  1. Nikolay Skvortsov
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  2. Sergey Stupnikov
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Editor information

Editors and Affiliations

  1. Voronezh State University, Voronezh, Russia

    Alexander Sychev

  2. Voronezh State University, Voronezh, Russia

    Sergey Makhortov

  3. Christian-Albrecht University of Kiel, Kiel, Schleswig-Holstein, Germany

    Bernhard Thalheim

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Skvortsov, N., Stupnikov, S. (2021). Managing Data-Intensive Research Problem-Solving Lifecycle. In: Sychev, A., Makhortov, S., Thalheim, B. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2020. Communications in Computer and Information Science, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-030-81200-3_1

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  • DOI: https://doi.org/10.1007/978-3-030-81200-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-81199-0

  • Online ISBN: 978-3-030-81200-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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