Exploring an innovative evaluation method to ensure the quality of spatial data needed at the distribution stage: focused on building and road map in South Korea
This paper aimed to suggest a method to evaluate the quality of spatial data in order to increase the interoperability of national geospatial data. The national geospatial data is managed by the government and is provided to the public according to the Spatial Data Industry Promotion Act. Although the quality control is necessary in the every processing steps including data production, processing, distribution, and service. This paper focused data quality only on the distribution stage. The evaluation rules suitable for national geospatial data were derived by comparing and analyzing domestic and foreign standards for data quality. Then, the quality diagnosis were carried out using commercial software. Two diagnostic methods were applied to test data quality. One is ‘Layer-based Approach’ that requires a comparison between two layers and the other is ‘Geometry-based Approach’ that diagnose feature geometries in a single layer. The diagnostic methods have been applied to the building and road layers in Seoul. In conclusion, this paper presented the standard quality evaluation rules and criteria that could be applied immediately for spatial data distribution industry, although some of items checked by direct visual inspection. Later, it is expected all quality evaluation rules are fully automated.
KeywordsNational geospatial information Data quality Quality evaluation Data distribution Data usability
- 1.Kim, J. (2012). A study on the quality certification of three-dimensional spatial information. Doctoral Dissertation, University of Seoul.Google Scholar
- 2.Gervais, M., et al. (2009). Data quality issues and geographic knowledge discovery. In H. J. Miller & J. Han (Eds.), Geographic data mining and knowledge discovery (2nd ed., pp. 99–115). Boca Raton, FL: CRC Press.Google Scholar
- 4.MOLIT. (2018). Implementation plan of the national spatial information policy in 2019. Seoul: Ministry of Land, Infrastructure and Transport.Google Scholar
- 5.Jung, Y. C. (2017). The data economy revitalization strategy in the fourth industrial revolution. Jincheon: Korea Information Society and Development Institute.Google Scholar
- 6.Wu, C. (2018). The Republic of Korea is going to be changed. Seoul: National Information Society Agency.Google Scholar
- 7.Lee, S. (2016). A study on the improvement of domestic R&D data quality management system. Doctoral Dissertation, University of Seoul.Google Scholar
- 8.NGII. (2015). Regulations for working with topologic map. Yeongtong: National Geographic Information Institute.Google Scholar
- 9.NGII. (2017). Regulations for performance test of public measurements. Yeongtong: National Geographic Information Institute.Google Scholar
- 10.Carson, C. (2000). What is data quality? A distillation of experience. Washington, DC: Statistics Department, International Monetary Fund. http://www.thecre.com/pdf/imf.pdf. Accessed 13 July 2019.
- 11.Caprioli, M., Scognamiglio, A., Strisciuglio, G., & Arantino, E. (2003). Rules and standards for spatial data quality in GIS environment. In Proceedings of the 21st international cartographic conference (ICC), Durban, South Africa.Google Scholar
- 13.Musungu, K. (2015) Assessing spatial data quality of participatory GIS studies: A case study in Cape Town. In Proceedings of the 2015 joint international geoinformation conference (pp. 75–82). Kuala Lumpur, Malaysia.Google Scholar
- 14.Ghose, M. K. (2002). Product quality assureance for GIS life-cycle. In: Proceedings of Map India.Google Scholar
- 16.Choi, Y., Heo, M., Bae, K., Park, J., Seo, C., Kim, J., et al. (2010). Research on the establishment of a system for quality certification of spatial information. Tokyo: Ministry of Land, Infrastructure, and Transport.Google Scholar
- 17.Kim, J., Choi, Y., Seo, J., & Jang, E. (2011). A basic study on the quality certification of spatial information equipment. Korean Journal of Spatial Information Society, 19(4), 33–43.Google Scholar
- 18.Jung, I. (2017). Quality evaluation methods and verification for enhancing the utilization of indoor spatial information. Doctoral Dissertation, University of Seoul.Google Scholar
- 20.Alibad, A. F., Shojaei, S., Zare, M., & Ekhtesasi, M. R. (2018). Assessment of the fuzzy ARTMAP neural network method performance in geological mapping using satellite images and Boolean logic. International Journal of Environmental Science and Technology. https://doi.org/10.1007/s13762-018-1795-7.Google Scholar
- 21.Hunter, G. J., Bregt, A. K., Heuvelink, G. B. M., Bruin, S. D., & Virrantaus, K. (2009). Spatial data quality: Problems and prospects. In G. Navratil (Ed.), Research trends in geographic information science. Berlin: Springer.Google Scholar
- 22.Environmental Systems Research Institute (ESRI). ArcGIS Online Help. http://desktop.arcgis.com/en/arcmap/10.3/manage-data/editingtopology/geodatabase-topology-rules-and-topology-error-fixes.htm. Accessed 7 July 2019.
- 23.Lee, B., & Lee, M. (2017). The subject and method of quality control of national geographic information. The Geographical Journal of Korea, 51(2), 135–148.Google Scholar