Analysis of Mashup Performances based on Vector Layer of Various GeoWeb 2.0 Platform Open APIs

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, Received (March 30, 2019), Review Result(April 9, 2019) Accepted(April 14, 2019), Published(April 30, 2019) Graduate Student, Dept. Computer Engineering, Daejeon Univ. 62 Daehak-ro Dong-gu Daejeon Korea E-mail: kjwon15@edu.dju.ac.kr (Corresponding Author) Associate Professor, Dept. Computer Engineering, Daejeon Univ. 62 Daehak-ro Dong-gu Daejeon Korea E-mail: minsoo@dju.kr *This research was supported by a grant(19DRMS-B147287-02) from development of customized realistic 3D geospatial information update and utilization technology based on consumer demand, funded by Ministry of Land, Infrastructure and Transport of Korean government. Analysis of Mashup Performances based on Vector Layer of Various GeoWeb 2.0 Platform Open APIs Copyright c 2019 HSST 746 OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.