Model for storing spatial data of tensor geophysical fields

Vorobeva G.R., Vorobev A.V., Orlov G.O. Model for storing spatial data of tensor geophysical fields. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2025, vol. 25, no. 3, pp. 565–573 (in Russian). doi: 10.17586/2226-1494-2025-25-3-565-573

It is known that geophysical fields (geomagnetic, gravitational and electromagnetic), when recorded or modeled, represent a set of several vector components characterizing the change in the corresponding parameters in space and time. Geophysical field data is currently stored based on known data models which usually have a relational structure. Analysis of known studies has shown the redundancy and inefficiency of this approach. This is reflected in the low speed of obtaining the desired data when using complex multi-predicate queries. The continuously growing volume and complexity of the data under consideration require new approaches to organizing their storage to improve the performance of information systems used to support decision-making based on geophysical field data. This paper proposes and examines a model for representing and storing geophysical field data that ensures increased performance of information systems. An analysis of specific features of geophysical fields due to their tensor nature is presented. The main data components are considered, promising options for combining known data models are determined to obtain the best result to improve the performance of the corresponding databases. A multi-axis model of geophysical field data is proposed that takes into account the tensor multi-component structure of the fields and combines the features of the hierarchical organization of data and element-centric information markup. A distinctive feature of the proposed model is the introduction of static and dynamic axes. This approach ensures the presentation of metadata, operational and archived data, and the interaction between them at the level of background processes with the participation of software triggers with temporal predicates. Using the example of geomagnetic field data and its variations, an increase in the speed of executing single- and multi-predicate queries for data selection and insertion of new records into the storage is demonstrated. Computational experiments comparing the proposed and known approaches to the organization and storage of geophysical field data on various sets and volumes of data showed that the implementation of the multi- axis data model allows increasing the speed of executing single-predicate queries by 25.7 %, multi-predicate queries by 20.1 %, and queries for inserting new records by 21.3 %. This allows us to conclude that the proposed solution is appropriate.

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