500 rub
Journal Highly available systems №1 for 2026 г.
Article in number:
Scenarios of semantic specification and reuse of data sources in research infrastructures
Type of article: scientific article
DOI: https://doi.org/10.18127/j20729472-202601-11
UDC: 004.654
Authors:

N.A. Skvortsov1

1 FRC CSC RAS (Moscow, Russia)

1 nskv@mail.ru

Abstract:

Problem statement. The heterogeneity of research data makes semantically grounded reuse particularly relevant. Research infrastructures require formal mechanisms for managing data, domain knowledge, and their reuse throughout the entire problem solving lifecycle.

Objective. The objective of the work is to develop scenarios for managing data sources and research results in infrastructures based on semantic specifications. It is necessary to ensure interoperability and reuse of data in solving research problems, as well as the accumulation of resources ready for multiple semantically grounded reuse. The work is aimed at formalizing the discovery, integration, and reuse of data and services using domain ontologies.

Results. An approach to managing data sources and research results based on formal ontologies and the concept of digital objects is proposed. Three key scenarios are described: semantic discovery and reuse of registered sources, registration and integration of external data and services, and reuse of research results. It is shown that semantic annotation, logical reasoning, and registration of resources in the form of digital objects ensure interoperability, accumulation, and correct reuse of resources.

Practical significance. The scenarios are oriented toward the development of research infrastructures taking into account the needs of specific domain areas. Research results are semantically linked to their domain context and become ready for reuse. This reduces duplication of efforts, increases reproducibility, and contributes to the formation of an extensible knowledge graph ensuring research continuity.

Pages: 56-60
For citation

Skvortsov N.A. Scenarios of semantic specification and reuse of data sources in research infrastructures. Highly Available Systems. 2026. V. 22. № 1. P. 56−60. DOI: https://doi.org/10.18127/j20729472-202601-11 (in Russian)

References
  1. De Smedt K., Koureas D., Wittenburg P. FAIR digital objects for science: From data pieces to actionable knowledge units. Publications. 2020. V. 8. № 2. Article number 21. 17 p. https://doi.org/10.3390/publications8020021
  2. Wilkinson M. et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 2016. V. 3. Article number 160018. https://doi.org/10.1038/sdata.2016.18
  3. Earth Science Information Partners (ESIP). https://www.esipfed.org/
  4. OpenAIRE Explore. https://explore.openaire.eu
  5. EOSC EU Node. https://open-science-cloud.ec.europa.eu/
  6. Baade F. et al. Introduction to description logic. Cambridge: Cambridge University Press. 2017.
  7. Skvortsov N., Stupnikov S. Managing data-intensive research problem-solving lifecycle. DAMDID/RCDL 2020. Springer, 2021. P. 3–18. https://doi.org/10.1007/978-3-030-81200-3_1
  8. Chaudhri V.K. et al. Knowledge graphs: Introduction, history, and perspectives. AI Magazine. 2022. V. 43. № 1. P. 17–29. https://doi.org/10.1002/aaai.12033
  9. Skvortsov N.A., Stupnikov S.A. A semantic approach to workflow management and reuse for research problem solving. Data Intelligence. 2022. V. 4. № 2. P. 439–454. https://doi.org/10.1162/dint_a_00142
  10. PROV-Overview: An overview of the PROV family of documents. W3C Working Group Note. 2013. http://www.w3.org/TR/prov-overview/
  11. Mason B. et al. The Washington Double Star Catalog. The Astronomical Journal. 2001. V. 122. № 6. https://doi.org/10.1086/323920
Date of receipt: 24.02.2026
Approved after review: 26.02.2026
Accepted for publication: 10.03.2026