JSON and MySQL Databases for Spatial Visualization of Polygon and Multipolygon Data in Geographic Information Systems: A Comparative Study

M. Zakki Abdillah^1*, Devi Astri Nawangnugraeni², Solikhin Solikhin³, Toni Wijanarko Adi Putra⁴

 Abstract

Purpose: Spatial data is used to display digital maps. Geographic information systems' access performance depends on spatial data formats. This study compared JSON and MySQL database data display speeds. Open-source RDBMSs work with various programming languages. JSON displays data in text format. The purpose of this study is to select spatial data for polygon and multipolygon Geographic Information Systems (GIS).

Design of study: access speed to the GIS determined the method. This study evaluated how effectively JSON and MySQL displayed digital maps in GIS using two types of geographical data. JSON was in the server directory, and MySQL was on the database server. To measure performance, these two spatial data sets were compared using the same server parameters. Testers employed various tools, operating systems, devices, and browsers.

Result: JSON data is stored on a live server and is easier to access while having more data. This test compares file size and speed on three online devices. This test generates JSON as the fastest geographic data, with an average access time of 3.9 seconds and 8.5 MB loaded. MySQL, which averages 9.7 seconds, loads 6.3 MB of files. Despite its larger file size, JSON is faster for spatial data, according to tests.

Originality: Its comparison of JSON and MySQL databases based on its application for geographical data display in GIS is unique. This test offers geographic data in JSON faster than MYSQL. JSON can be used to choose location data that GIS can readily access.

DOI : https://doi.org/10.15294/sji.v10i4.47393

Full Text: PDF

References

A. A. Nurdin, G. N. Salmi, K. Sentosa, A. R. Wijayanti, and A. Prasetya, “Utilization of Business Intelligence in Sales Information Systems,” J. Inf. Syst. Explor. Res., vol. 1, no. 1, pp. 39–48, 2022, doi: 10.52465/joiser.v1i1.101.

R. Naufalia, C. Lateefa, and D. Yassar, “Usefulness factors to predict the continuance intention using mobile payment, case study: GO-Pay, OVO, Dana,” J. Soft Comput. Explor., vol. 2, no. 2, 2021, doi: 10.52465/joscex.v2i2.50.

W. A. Teniwut, C. L. Hasyim, and F. Pentury, “Towards smart government for sustainable fisheries and marine development: An intelligent web-based support system approach in small islands,” Mar. Policy, vol. 143, no. May, p. 105158, 2022, doi: 10.1016/j.marpol.2022.105158.

M. Kulawiak, A. Dawidowicz, and M. E. Pacholczyk, “Analysis of server-side and client-side WebGIS data processing methods on the example of JTS and JSTS using open data from OSM and geoportal,” Comput. Geosci., vol. 129, no. April, pp. 26–37, 2019, doi: 10.1016/j.cageo.2019.04.011.

J. Shi, Z. Pan, L. Jiang, and X. Zhai, “An ontology-based methodology to establish city information model of digital twin city by merging BIM, GIS and IoT,” Adv. Eng. Informatics, vol. 57, no. November 2022, p. 102114, 2023, doi: 10.1016/j.aei.2023.102114.

S. Sularno, R. Astri, P. Anggraini, D. Prima Mulya, and D. Mulya, “Geographical Information System of Bus and Travel Counter in Padang City Using BFS Method Based on Mobile Web,” Sci. J. Informatics, vol. 8, no. 2, pp. 304–313, 2021, doi: 10.15294/sji.v8i2.33117.

J. L. Amaro-Mellado, L. Melgar-García, C. Rubio-Escudero, and D. Gutiérrez-Avilés, “Generating a seismogenic source zone model for the Pyrenees: A GIS-assisted triclustering approach,” Comput. Geosci., vol. 150, no. February, p. 104736, 2021, doi: 10.1016/j.cageo.2021.104736.

M. Z. Abdillah, D. A. Nawangnugraeni, and A. H. P. Yuniarto, “Geographic Information System (GIS) For Maping Greenpark Using Leaflet JS,” J. Tek. Inform. Kaputama, vol. 5, no. 2, pp. 259–266, 2021.

S. Singh and S. N. Behera, Advances in Waste Management, no. January. Springer Singapore, 2019. doi: 10.1007/978-981-13-0215-2.

P. Du and H. Hu, “Optimization of tourism route planning algorithm for forest wetland based on GIS,” J. Discret. Math. Sci. Cryptogr., vol. 21, no. 2, pp. 283–288, 2018, doi: 10.1080/09720529.2018.1449300.

S. W. Mulvenon, K. Wang, S. McKenzie, and T. Anderson, “Spatially Referenced Educational Achievement Data Exploration: A Web-Based Interactive System Integration of GIS, PHP, and MySQL Technologies,” J. Educ. Technol. Syst., vol. 34, no. 3, pp. 243–256, Mar. 2006, doi: 10.2190/2VUC-CCJN-LHB3-EU7J.

J. Jumadi and S. Widiadi, “Pengembangan Aplikasi Sistem Informasi Geografis (SIG) berbasis Web untuk Manajemen Pemanfaatan Air Tanah menggunakan PHP, Java dan MySQL Spatial (Studi Kasus di Kabupaten Banyumas),” Forum Geogr., vol. 23, no. 2, p. 1236, Dec. 2009, doi: 10.23917/forgeo.v23i2.5006.

S. Q. Khairunisa et al., “Characterization of spatial and temporal transmission of HIV infection in Surabaya, Indonesia: Geographic information system (GIS) cluster detection analysis (2016–2020),” Heliyon, vol. 9, no. 9, p. e19528, 2023, doi: 10.1016/j.heliyon.2023.e19528.

C. Quiros, P. K. Thornton, M. Herrero, A. Notenbaert, and E. Gonzalez-Estrada, “GOBLET: An open-source geographic overlaying database and query module for spatial targeting in agricultural systems,” Comput. Electron. Agric., vol. 68, no. 1, pp. 114–128, Aug. 2009, doi: 10.1016/j.compag.2009.05.001.

G. Zodiatis, E. Zhuk, V. Krylenko, and M. Krylenko, “Dolgaya spit dynamics visualization by using Black Sea GIS regional module,” in Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), Aug. 2018, p. 61. doi: 10.1117/12.2326496.

A. Azzam, G. Samy, M. A. Hagras, and R. ElKholy, “Geographic information systems-based framework for water–energy–food nexus assessments,” Ain Shams Eng. J., p. 102224, Mar. 2023, doi: 10.1016/j.asej.2023.102224.

F. Medjani, T. Derradji, F. Zahi, M. Djidel, S. Labar, and L. Bouchagoura, “Assessment of soil erosion by Universal Soil Loss Equation model based on Geographic Information System data: a case study of the Mafragh watershed, north-eastern Algeria,” Sci. African, vol. 21, p. e01782, Sep. 2023, doi: 10.1016/j.sciaf.2023.e01782.

J. Penny, D. Khadka, P. B. R. Alves, A. S. Chen, and S. Djordjević, “Using multi criteria decision analysis in a geographical information system framework to assess drought risk,” Water Res. X, vol. 20, p. 100190, Sep. 2023, doi: 10.1016/j.wroa.2023.100190.

L. Vankova, Z. Krejza, G. Kocourkova, and J. Laciga, “Geographic Information System Usage Options in Facility Management,” Procedia Comput. Sci., vol. 196, pp. 708–716, 2022, doi: 10.1016/j.procs.2021.12.067.

S. W. Chan, S. K. Abid, N. Sulaiman, U. Nazir, and K. Azam, “A systematic review of the floodvulnerability using geographic information system,” Heliyon, vol. 8, no. 3, p. e09075, Mar. 2022, doi: 10.1016/j.heliyon.2022.e09075.

F. J. Fliegner and D. Möst, “High-resolution scenario building support for offshore grid development studies in a geographical information system,” Energy Strateg. Rev., vol. 48, p. 101110, Jul. 2023, doi: 10.1016/j.esr.2023.101110.

G. Villacreses, J. Martínez-Gómez, D. Jijón, and M. Cordovez, “Geolocation of photovoltaic farms using Geographic Information Systems (GIS) with Multiple-criteria decision-making (MCDM) methods: Case of the Ecuadorian energy regulation,” Energy Reports, vol. 8, pp. 3526–3548, Nov. 2022, doi: 10.1016/j.egyr.2022.02.152.

J. Zhang, X. Zhang, A. Rentizelas, C. Dong, and J. Li, “Optimisation of Logistic Model Using Geographic Information Systems: A Case Study of Biomass-based Combined Heat & Power Generation in China,” Appl. Energy Combust. Sci., vol. 10, p. 100060, Jun. 2022, doi: 10.1016/j.jaecs.2022.100060.

S. Boroushaki and J. Malczewski, “ParticipatoryGlS: a web-based collaborative GIS and multicriteria decision analysis,” Urisa J., vol. 22, no. 1, p. 23, 2010.

C.-O. Truică, E.-S. Apostol, J. Darmont, and T. B. Pedersen, “The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes,” Big Data Res., vol. 25, p. 100205, Jul. 2021, doi: 10.1016/j.bdr.2021.100205.

M.-A. Baazizi, D. Colazzo, G. Ghelli, C. Sartiani, and S. Scherzinger, “Negation-closure for JSON Schema,” Theor. Comput. Sci., vol. 955, p. 113823, Apr. 2023, doi: 10.1016/j.tcs.2023.113823.

Zhuokui Xu and Jianjun Zhu, “Research of WebGIS based on HTML5 and JSON,” in Proceedings of 2011 International Conference on Computer Science and Network Technology, Dec. 2011, pp. 1714–1717. doi: 10.1109/ICCSNT.2011.6182298.

J. Maso, A. Z. Torres, and P. Baumann, “New Model for Geospatial Coverages in JSON,” 2019, pp. 316–357. doi: 10.4018/978-1-5225-8446-9.ch015.

A. A. Frozza and R. dos S. Mello, “JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases,” Geoinformatica, vol. 24, no. 4, pp. 987–1019, Oct. 2020, doi: 10.1007/s10707-020-00415-w.

P. Bourhis, J. L. Reutter, and D. Vrgoč, “JSON: Data model and query languages,” Inf. Syst., vol. 89, p. 101478, Mar. 2020, doi: 10.1016/j.is.2019.101478.

M. Z. Abdillah, “Implementation of AJAX and JSON to improve web application performance,” J. Transform., vol. 14, no. 1, p. 1, Nov. 2016, doi: 10.26623/transformatika.v14i1.363.

F. da Costa Rainho and J. Bernardino, “Web GIS: A new system to store spatial data using GeoJSON in MongoDB,” in 2018 13th Iberian Conference on Information Systems and Technologies (CISTI), Jun. 2018, pp. 1–6. doi: 10.23919/CISTI.2018.8399279.

Gunawan, F. X. Ferdinandus, and E. I. Setiawan, “GeoJSON Web Service based road assets management system for Surabaya city using mobile GPS,” in 2016 International Computer Science and Engineering Conference (ICSEC), Dec. 2016, pp. 1–5. doi: 10.1109/ICSEC.2016.7859915.

Z. Zhu and J. Tan, “A Multi-Source Heterogeneous Vector Space Data Integration Scheme Based on GeoJSON,” in 2018 26th International Conference on Geoinformatics, Jun. 2018, pp. 1–4. doi: 10.1109/GEOINFORMATICS.2018.8557141.

Y. K. Gupta, R. D. Gupta, and K. Kumar, “WebGIS for Planning Infrastructural Facilities at Village Level,” in 13th Annual International Conference and Exhibition on Geospatial Information Technology and Applications, 2010, pp. 19–21.

Y. P. Singh, A. K. Singh, and R. P. Singh, “Web GIS based Framework for Citizen Reporting on Collection of Solid Waste and Mapping in GIS for Allahabad City,” SAMRIDDHI A J. Phys. Sci. Eng. Technol., vol. 8, no. 01, pp. 01–05, Jun. 2016, doi: 10.18090/samriddhi.v8i1.11405.

A. T. Kulkarni, J. Mohanty, T. I. Eldho, E. P. Rao, and B. K. Mohan, “A web GIS based integrated flood assessment modeling tool for coastal urban watersheds,” Comput. Geosci., vol. 64, pp. 7–14, Mar. 2014, doi: 10.1016/j.cageo.2013.11.002.

I. K. G. Sudiartha, I. N. E. Indrayana, I. W. Suasnawa, S. A. Asri, and P. W. Sunu, “Data Structure Comparison Between MySql Relational Database and Firebase Database NoSql on Mobile Based Tourist Tracking Application,” J. Phys. Conf. Ser., vol. 1569, p. 032092, Jul. 2020, doi: 10.1088/1742-6596/1569/3/032092.

M. Ohyver, J. V. Moniaga, I. Sungkawa, B. E. Subagyo, and I. A. Chandra, “The Comparison Firebase Realtime Database and MySQL Database Performance using Wilcoxon Signed-Rank Test,” Procedia Comput. Sci., vol. 157, pp. 396–405, 2019, doi: 10.1016/j.procs.2019.08.231.

E. Zhuk, A. Khaliulin, G. Zodiatis, A. Nikolaidis, and E. Isaeva, “Black Sea GIS developed in MHI,” in Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016), Aug. 2016, p. 96881C. doi: 10.1117/12.2241631.