Integrated Processing of Spatial Information based on Multidimensional Data Models for General Planning Tasks
Keywords:multidimensional information objects, multidimensional data model, building information modelling, general planning tasks
The article presents the development of method of integrated spatial information processing based on multidimensional data models. Joint description of spatial data of different levels of detail (LOD) using a multidimensional model and attribute data using a relational model is difficult and requires the development of modified structures of multidimensional data models. The description of spatial and attribute data based on multidimensional information objects (MIO) is determined. It is proposed to use a new type of MIO - modified multidimensional information objects (MMIO). MIO and MMIO schemes allow describing multidimensional information objects and relationships in the form of a single multidimensional structure. On the basis of the introduced method of joint description of spatial and attributive data using extended multidimensional information objects, a multidimensional data model is built. This approach allows integrating different types of databases and contains a unified description of spatial and attribute data in the form of a multidimensional information object. The developed method is supposed to be used in BIM (Building Information Modeling) technology of computer modeling to solve general planning tasks.
J. Wang, H.Y. Chong, W. Shou, X. Wang, J. Guo, “BIM-enabled design collaboration for complex building,” Cooperative Design, Visualization, and Engineering, Springer, 2014, pp. 238-244. https://doi.org/10.1007/978-3-319-10831-5_35.
E. F. Codd, S. B. Codd, C.T. Salley, Providing OLAP (OnLine Analytical Processing) to User-Analysts: An IT Mandate,” E.F. Codd @ Associates, 1993, 24 p.
V. A. Pavlov, B. A. Novikov, “Array database internals,” Trudy ISP RAN/Proc. ISP RAS, vol. 30, issue 1, pp. 137-160, 2018. https://doi.org/10.15514/ISPRAS-2018-30(1)-10.
O. I. Hristodulo, “A joint description of spatial and attribute data based on multidimensional information objects,” Software Products and Systems, no. 3(95), pp. 48–54, 2011. (in Russian)
T.A. Honcharenko, V.M. Mihaylenko, “Set-theoretic description of spatial data in the information model of the construction territory,” Herald of the National Technical University “KhPI”. Subject issue: Information Science and Modelling. Kharkiv: NTU “KhPI”, vol. 24 (1300), pp. 157-167, 2018. https://doi.org/10.20998/2411-0558.2018.24.13. (in Ukrainian)
R. B. Kravets, Organization of the Multidimensional Implementation and Analysis in Data Related Bases, 2006, [Online]. Available at: http://ena.lp.edu.ua/bitstream/ntb/9816/1/18.pdf. (in Ukrainian)
P. Garcia-Soidan, R. Menezes, O. Rubinos, “Approaches for spatial data,” Stochastic Environmental Research and Risk Assessment, vol. 28, pp. 1207-1219, 2014. https://doi.org/10.1007/s00477-013-0808-9.
Alkathiri, M., Jhummarwala, A. & Potdar, M.B. “Multi-dimensional geospatial data mining in a distributed environment using MapReduce,” J Big Data, vol. 6, pp. 82-90, 2019. https://doi.org/10.1186/s40537-019-0245-9.
A. V. Medvedev, E. A. Chzhan, “On nonparametric modelling of multidimensional noninertial systems with delay,” Bulletin of the South Ural State University. Ser. Mathematical Modelling, Programming & Computer Software, vol. 10, no. 2, pp. 124136, 2017. https://doi.org/10.14529/mmp170210.
M. R. Evans, D. Oliver, K. Yang, X. Zhou, R. Y. Ali, S. Shekhar, “Enabling spatial big data via CyberGIS: challenges and opportunities,” In: Wang S., Goodchild M. (eds) CyberGIS for Geospatial Discovery and Innovation. GeoJournal Library, vol 118. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1531-5_8.
M.C. Hout, S.D. Goldinger, R.W. Ferguson, “The versatility of SpAM: A fast, efficient spatial method of data collection for multidimensional scaling,” J Exp Psychol Gen, vol. 142, pp. 256–281, 2013. https://doi.org/10.1037/a0028860.
N. Jaworska, A. Chupetlovska-Anastasova, “A review of multidimensional scaling (MDS) and its utility in various psychological domains,” Tutor Quant Methods Psychol., vol. 5, pp. 1–10, 2009. https://doi.org/10.20982/tqmp.05.1.p001.
M.S. Oh, “A simple and efficient Bayesian procedure for selecting dimensionality in multidimensional scaling,” J Multivar Anal, vol. 107, pp. 200–209, 2011. https://doi.org/10.1016/j.jmva.2012.01.012.
N. Kriegeskorte, M. Mur, “Inverse MDS: Inferring dissimilarity structure from multiple item arrangements,” Front Psychol., vol. 3, pp. 1–12, 2012. https://doi.org/10.3389/fpsyg.2012.00245.
E.M. Migo, D. Montaldi, A.R. Mayes, “A visual object stimulus database with standardized similarity information,” Behav. Res. Methods, vol. 145, pp. 344–354, 2013. https://doi.org/10.3758/s13428-012-0255-4.
G. Samson, J. Lu, Q. Xu, “Large spatial datasets: present challenges, future opportunities,” Proceedings of the International Conference on Change, Innovation, Informatics and Disruptive Technology ICCIIDT’16, London, UK, October 11-12, 2016, pp. 204–217.
W. Peng, M.O. Ward, E.A. Rundensteiner, “Clutter reduction in multi-dimensional data visualization using dimension reordering,” Proceedings of the IEEE Symposium on Information Visualization, 2004, pp. 89-96.
L. Alarabi, M. F. Mokbel, M. Musleh, “Sthadoop: a Mapreduce framework for spatiotemporal data,” GeoInformatica, vol. 22, pp. 785–813, 2018. https://doi.org/10.1007/s10707-018-0325-6.
O. Terentyev, S. Tsiutsiura, T. Honcharenko, T. Lyashchenko, “Multidimensional space structure for adaptable data model,” International Journal of Recent Technology and Engineering (IJRTE), vol. 8, issue 3, pp. 7753-7758, 2019. https://doi.org/10.35940/ijrte.C6318.098319.
Т. Honcharenko, Y.Chupryna, I. Ivakhnenko, M. Zinchenco, T. Tsyfra, “Reengineering of the construction companies based on BIM-technology,” International Journal on Emerging Trends in Engineering Research, vol. 8, issue 8, pp. 4166-4172, 2020. https://doi.org/10.30534/ijeter/2020/22882020.
J. C. P. Cheng, Q. Lu, Y. Deng, “Analytical Review and Evaluation of Civil Information Modeling”, Automation In Construction, vol. 67, 31—47, 2016. https://doi.org/10.1016/j.autcon.2016.02.006.
M. Dyomin, A. Dmytrenko, D. Chernyshev, O. Ivashko, “Big Cities Industrial Territories Revitalization Problems and Ways of Their Solution”, Lecture Notes in Civil Engineering, vol. 73, pp. 365-373, 2020.
S. Azhar, A. Behringer, “A BIM-based approach for communicating and implementing a construction site safety plan”, 49th ASC Annual International Conference Proceedings, Associated Schools of Construction, 2013. https://ascpro0.ascweb.org/archives/cd/2013/paper/CPRT43002013.pdf.
Y. Tan, Y. Fang, T. Zhou, V.J.L. Gan, J.C.P. Cheng, “BIM-supported 4D acoustics simulation approach to mitigating noise impact on maintenance workers on offshore oil and gas platforms”, Automation In Construction, vol. 100, 1—10, 2019. https://doi.org/10.1016/j.autcon.2018.12.019.
M. Shkuro, S. Bushuyev, “Development of proactive method of communications for projects of ensuring the energy efficiency of municipal infrastructure”, Eureka Physics and Engineering, vol. 1, pp. 3-12, 2019. https://dx.doi.org/10.21303/2461-4262.2019.00826.
K. Chen, W. Chen, C.T. Li, J.C.P Cheng, “A BIM-based location aware AR collaborative framework for facility maintenance management”, Journal of Information Technology in Construction, vol. 24, pp.360-380, 2019. https://doi.org/10.36680/j.itcon.2019.019.
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