Multi-axis model of geophysical data: concept, formalization, implementation | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2025. № 71. DOI: 10.17223/19988605/71/7

Multi-axis model of geophysical data: concept, formalization, implementation

It is known that geophysical fields (geomagnetic, gravitational and electromagnetic) in the context of recorded or modeled data are a set of several coaxial vector components characterizing the change in the corresponding parameter in space and time. Currently practiced approaches to organizing the storage of such data are based, as a rule, on one of the data models. At the same time, joint storage of source metadata and geophysical data directly in many cases is associated with inefficient use of associated computing resources. This paper considers an approach focused on separate storage, but joint complex application of metadata and data of geophysical field recording tools, taking into account their multi-vector nature and tensor representation of the analyzed parameters. Using the example of the geomagnetic field, the effectiveness of the proposed approach is considered in the context of optimizing data storage, on the one hand, and increasing the computational speed of executing queries to them, on the other. Contribution of the authors: the authors contributed equally to this article. The authors declare no conflicts of interests.

Download file
Counter downloads: 7

Keywords

geophysical data, tensor field, vector field, data storage, processing and manipulation of applied data

Authors

NameOrganizationE-mail
Vorobeva Gulnara R.Ufa University of Science and TechnologyGulnara.vorobeva@gmail.com
Vorobev Andrey V.Ufa University of Science and TechnologyGeomagnet@list.ru
Orlov Gleb O.Ufa University of Science and Technologyorlovgleb99@mail.ru
Всего: 3

References

Geomagnetic Observations and Models / M. Mandea, M. Korte (eds). Dordrecht : Springer, 2011. (lAGA Special Sopron Book Series; 5).
INTERMAGNET technical reference manual. Version 4.6 / ed. by S.-L. Benoit. Edinburgh : INTERMAGNET. BGS, 2012.
Califf S., Alken P., Chulliat A., Anderson B., Rock K., Vines S., Barnes R., Liou K. Investigation of geomagnetic reference models based on the Iridium constellation // Earth, Planets and Space. 2022. V. 1 (74). P. 1-21. doi: 10.1186/s40623-022-01574-w.
Lazzeri C., Samsonov A., Forsyth C., Branduardi-Raymont G., Bogdanova Yu. A Statistical Study of the Properties of, and Geo magnetic Responses to, Large, Rapid Southward Turnings of the Interplanetary Magnetic Field // J. of Geophysical Research:.
Peng Z., Laramee S. Higher Dimensional Vector Field Visualization. A Survey // Theory and Practice of Computer Graphics (TPCG ‘09). 2009. P. 149-163.
Hergl C., Blecha C., Kretzschmar V., Raith F., Gunther F., Stommel M., Jankowai J., Hotz I., Nagel T., Scheuermann G. Visualization of Tensor Fields in Mechanics // Computer Graphics Forum. 2021. V. 40 (6). P. 135-161. doi: 10.1111/cgf.14209.
Jilesh V., Pournami A. On a generalization of Laplace distribution with applications.International // J. of Data Science and Analytics. 2025. V. 19 (1). P. 1-10. doi: 10.1007/s41060-024-00706-7.
He Z., Hu X., Teng Yu., Zhang X., Shen X. Data agreement analysis and correction of comparative geomagnetic vector observations // Earth, Planets and Space. 2022. V. 74 (1). Art. 29. doi: 10.1186/s40623-022-01583-9.
Huang Y., Wu L., Li D. Theoretical Research on Full Attitude Determination Using Geomagnetic Gradient Tensor // The J. of Navigation. 2015. V. 68 (5). P. 951-961. doi: 10.1017/S0373463315000259.
Paulo O., Chuangjie X. On the Herbrand functional interpretation // Mathematical Logic Quarterly. 2020. V. 66 (1). P. 91-98. doi: 10.1002/malq.201900067.
Воробьев А.В., Воробьева Г.Р. Индуктивный метод восстановления временных рядов геомагнитных данных // Трудяг СПИИРАН. 2018. № 2 (57). С. 104-133. doi: 10.15622/sp.57.5.
Воробьев А.В., Воробьева Г.Р. Оценка влияния геомагнитной активности на метрологические характеристики инклино-метрических информационно-измерительных систем // Измерительная техника. 2017. № 6. С. 21-24.
Vorobev A.V., Vorobeva G.R., Yusupova N.I. Conception of geomagnetic data integrated space // SPIIRAS Proceedings. 2019. V. 18 (2). P. 390-415. doi: 10.15622/sp.18.2.390-415.
Ali M., Khan M. Enhancing XML Data Parsing and Querying Performance on Multi-Core Architectures // Statistics Computing and Interdisciplinary Research. 2024. V. 6 (1). P. 75-89. doi: 10.52700/scir.v6i1.158.
Воробьев А.В., Воробьева Г.Р. Подход к обнаружению и устранению артефактов пространственных изолиний в приложениях Веб-ГИС // Компьютерная оптика. 2023. Т. 47, № 1. С. 126-136. doi: 10.18287/2412-6179-CO-1127.
Воробьев А.В., Воробьева Г.Р. Подход к динамической визуализации разнородных геопространственных векторных изображений // Компьютерная оптика. 2024. Т. 48, № 1. С. 123-138. doi: 10.18287/2412-6179-CO-1279.
Jamal S., Rahman C., Abdulkarim M. XML Schema Validation Using Java API for XML Processing // UKH Journal of Science and Engineering. 2022. № 6. P. 33-41. doi: 10.25079/ukhjse.v6n1y2022.
Chen R., Wang Z., Su H., Xie S., Wang Z. Parallel XPath query based on cost optimization // The Journal of Supercomputing. 2022. V. 78 (2). P. 1-30. doi: 10.1007/s11227-021-04074-y.
Areces C., Fervari R. Axiomatizing Hybrid XPath with Data // Logical Methods in Computer Science. 2021. V. 17 (3). P. 1-37. doi: 10.46298/lmcs-17(3:5)2021.
Chernenkiy V.M., Gapanyuk Y.E., Kaganov Y.T., Dunin I.V., Lyaskovsky M.A., Larionov V. Storing Metagraph Model in Relational, Document-Oriented, and Graph Databases // Selected Papers of the XX International Conference on Data Analytics and Management in Data Intensive Domains. 2018. V. 2277. P. 82-89.
Terekhov V., Gapanyuk Y., Kanev A. Metagraph representation for overcoming limitations of existing knowledge bases // 28th Conference of Open Innovations Association (FRUCT). IEEE, 2021. P. 458-464.
Zichar M. Geovisualization based upon KML // Journal of Agricultural Informatics. 2021. V. 3 (1). P. 19-26. doi: 10.17700/jai.2012.3.1.49.
Ortinez A., Ruiz S., Luis G., Ortega E., Garcia-Reynoso A., Peralta O., Lopez-Gaona A., Castro T., Martinez Arroyo A. Emission inventory point source visualization on Google Earth and integrated with HYSPLIT model // Atmosfera. 2020. V. 34 (2). P. 1-36. doi: 10.20937/ATM.52834.
 Multi-axis model of geophysical data: concept, formalization, implementation | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2025. № 71. DOI: 10.17223/19988605/71/7

Multi-axis model of geophysical data: concept, formalization, implementation | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2025. № 71. DOI: 10.17223/19988605/71/7

Download full-text version
Counter downloads: 36