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GeoGraphNetworks: A comprehensive benchmark dataset for accurate and scalable graphical representations
Harish Sharma1, Peter Mooney1, Edgar Galván1
1Naturally Inspired Computation Research Group and Hamilton Institute, Department of Computer Science, National University of Ireland Maynooth, Maynooth, Ireland.
GeoGraphNetworks provides 110 validated spatial networks for road, rail, and river systems. This data repository simplifies geospatial processing for transportation and urban planning research.
Area of Science:
- Geographic Information Systems (GIS)
- Network Science
- Computational Geography
Background:
- Accurate spatial networks are crucial for transportation, urban planning, ecology, and network science research.
- ESRI Shapefiles, a common geospatial data source, require complex processing for network analysis.
Purpose of the Study:
- To present the GeoGraphNetworks data repository, offering validated spatial networks.
- To reduce technical barriers in geospatial processing for researchers.
Main Methods:
- Compiled 110 validated spatial networks for road, rail, and river systems.
- Provided graph representations in JSON and XLSX formats.
- Included detailed geographic information: node coordinates, edge connectivity, and lengths.
Main Results:
- The GeoGraphNetworks repository offers ready-to-use spatial network data.
- Eliminates the need for complex geospatial processing for users.
- Facilitates immediate application across various programming environments.
Conclusions:
- GeoGraphNetworks lowers technical barriers for spatial network research.
- Supports reproducible and scalable research across multiple disciplines.
- Enhances accessibility of spatial network resources for scientific inquiry.
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