Client-side versus server-side geographic data processing performance comparison: Data and code

The data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-poi...

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Bibliographic Details
Published in:Data in brief Vol. 26; p. 104507
Main Author: Kulawiak, Marcin
Format: Journal Article
Language:English
Published: Elsevier Inc 01.10.2019
Elsevier
Subjects:
Baltic Sea
computer software
data collection
Earth and Planetary Science
geographic information systems
Geoprocessing
GIS
Poland
Scalability
topology
Web
Poland
Baltic Sea
GIS
Geoprocessing
Scalability
Performance
Web
ISSN:2352-3409, 2352-3409
Online Access:Get full text
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Summary:The data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area of Tricity in northern Poland as well as Polish Exclusive Economic Zone of the Baltic Sea. They have been converted to a common Spherical Mercator projection coordinate system (EPSG:3857) and consist of vector features without attributes. They are provided in the form of single GeoJSON files containing multi-feature objects which can be processed by client-side as well as server-side algorithms in a single request. The provided javascript code exemplifies the application of those datasets for measurement of client-side and server-side geoprocessing performance by using algorithms implemented as part of Java Topology Suite (JTS) and Javascript Topology Suite (JSTS). The combination of data and code samples constitutes a universal benchmark for investigative analysis of geographic data processing algorithms and their implementations in different software system architectures.
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ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2019.104507