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

## TL;DR

This paper provides a dataset of graphlet decomposition for Tallinn's road network using 2020 OpenStreetMap data to analyze urban street patterns.

## Contribution

The paper introduces a reproducible method and dataset for analyzing urban street structures using graphlet decomposition.

## Key findings

- The dataset includes counts of all four-node graphlet configurations for each intersection in Tallinn's road network.
- The methodology uses Python and PyORCA to enable analysis of urban morphology and structural similarities.
- The dataset supports urban planning and transportation studies through accessible CSV and Shapefile formats.

## 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.