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An Ontology-Driven Approach to the Analytical Platform Development for Data-Intensive Domains

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Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1718))

Abstract

The development and support of knowledge-based systems for experts in the field of social network analysis is complicated by the problems of viability maintenance inevitably emerging in data intensive domains. Largely this is the case due to the properties of semistructured objects and processes that are analyzed by data specialists using data mining techniques and other automated analytical tools. In order to be viable a modern knowledge-based analytical platform should be able to integrate heterogeneous information, present it to users in an understandable way and support tools for functionality extensibility. In this paper we introduce an ontological approach to analytical platform development. Common requirements for analytical platform have been identified and substantiated. Theoretical basis of the proposed approach is described. General structure of the knowledge base is designed. The core of the platform is the multifaceted ontology including data ontologies describing data sources and data types and structures, problem ontologies describing specific user’s tasks, domain ontologies. Ontology-based domain-specific modeling tools are the part of analytical platform software too. The information integration method, design patterns for developing analytical platform core functionality such as ontology repository management, domain-specific languages generation and source code round-trip synchronization with DSL-models are proposed. Diagrams and schemes are included to paper to illustrate approach description.

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Authors and Affiliations

  1. HSE University, Studencheskaya Str. 38, 614070, Perm, Russia

    Viktor S. Zayakin, Lyudmila N. Lyadova, Viacheslav V. Lanin & Elena B. Zamyatina

  2. SEUSLAB LLC, Shosse Kosmonavtov Str. 111 (Building 27), 614066, Perm, Russia

    Viktor S. Zayakin & Evgeniy A. Rabchevskiy

Authors
  1. Viktor S. Zayakin
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  2. Lyudmila N. Lyadova
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  3. Viacheslav V. Lanin
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  4. Elena B. Zamyatina
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  5. Evgeniy A. Rabchevskiy
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Corresponding author

Correspondence to Lyudmila N. Lyadova .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

  2. Universidade da Madeira, Funchal, Portugal

    David Aveiro

  3. Delft University of Technology, Delft, The Netherlands

    Jan Dietz

  4. Polytechnic Institute of Coimbra - ISEC, Coimbra, Portugal

    Jorge Bernardino

  5. University of Naples Federico II, Naples, Italy

    Elio Masciari

  6. Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Zayakin, V.S., Lyadova, L.N., Lanin, V.V., Zamyatina, E.B., Rabchevskiy, E.A. (2023). An Ontology-Driven Approach to the Analytical Platform Development for Data-Intensive Domains. In: Fred, A., Aveiro, D., Dietz, J., Bernardino, J., Masciari, E., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2021. Communications in Computer and Information Science, vol 1718. Springer, Cham. https://doi.org/10.1007/978-3-031-35924-8_8

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  • DOI: https://doi.org/10.1007/978-3-031-35924-8_8

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