Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap data

This paper presents a comprehensive dataset of graphlet decomposition for the road network of Tallinn, Estonia, based on OpenStreetMap (OSM) data representing the road network state as of 1 January 2020. Graphlets, which are small subgraphs, serve as powerful tools for analyzing and classifying local street structures in urban networks. The dataset includes counts of all possible four-node graphlet configurations for each intersection in the road network, provided in both Comma Separated Values (CSV) and Environmental Systems Research Institute (ESRI) Shapefile formats for maximum accessibility. The methodology for extracting these graphlets using Python and the Python ORbit Counting Algorithm (PyORCA) library is explained in details. The processing pipeline includes graph construction from spatial data, node-centric graphlet counting, and conversion back to geographic format. The resulting dataset enables researchers to identify recurring patterns in urban street networks, study urban morphology, and compare structural similarities between different urban areas. The code is designed for reproducibility, allowing researchers to apply the same analysis to other cities. This dataset contributes to the growing field of quantitative urban morphology and can support studies in urban planning, transportation network analysis, sustainable development, and comparative urban studies.

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Publication Details

Journal
Data in Brief
Published
2025-06-13
DOI
https://doi.org/10.1016/j.dib.2025.111776
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap data

Mahdi Rasoulinezhad, Jenni Partanen, Nasim Eslamirad
Data in Brief
Data Management and Algorithms
article

Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap data

Mahdi Rasoulinezhad, Jenni Partanen, Nasim Eslamirad
article en

Abstract

This paper presents a comprehensive dataset of graphlet decomposition for the road network of Tallinn, Estonia, based on OpenStreetMap (OSM) data representing the road network state as of 1 January 2020. Graphlets, which are small subgraphs, serve as powerful tools for analyzing and classifying local street structures in urban networks. The dataset includes counts of all possible four-node graphlet configurations for each intersection in the road network, provided in both Comma Separated Values (CSV) and Environmental Systems Research Institute (ESRI) Shapefile formats for maximum accessibility. The methodology for extracting these graphlets using Python and the Python ORbit Counting Algorithm (PyORCA) library is explained in details. The processing pipeline includes graph construction from spatial data, node-centric graphlet counting, and conversion back to geographic format. The resulting dataset enables researchers to identify recurring patterns in urban street networks, study urban morphology, and compare structural similarities between different urban areas. The code is designed for reproducibility, allowing researchers to apply the same analysis to other cities. This dataset contributes to the growing field of quantitative urban morphology and can support studies in urban planning, transportation network analysis, sustainable development, and comparative urban studies.

Data in BriefVol. 61
University College Dublin (IE), Tallinn University of Technology (EE), Aalto University (FI)
Sustainable cities and communities
Openalex Percentile: Top 85%
Data Management and Algorithms
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Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap data — Mahdi Rasoulinezhad, Jenni Partanen, et al. · Data in Brief (2025) | TGRS Research Map | TGRS