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Network Science and Graph Analytics

Urban Graph Networks



This article is structured as follows. We begin by introducing how OpenStreetMap works and how we can receive data via python. Then, we discover how we can display data via python’s folium library. Afterwards we deep dive into graph theory and its applications. For instance, routing via Dijkstra’s algorithm and approaching the Traveling Salesman Problem are the final steps towards a data-informed optimized trip visiting Berlin’s famous spots. You will learn:how OpenStreetMaps data model works,
how Coordinate Reference Systems work, basics of Graph Theory and its algorithmic challenges, as well as, how to draw beautiful maps with python’s folium library.

Before we start, let’s find out how OpenStreetMap’s data model works. Basically, its data model consists of nodes, ways and _relations._For instance, nodes do have a specific position determined via latitude and longitude, like a tree, a bench, or a corner of a building. Tags and comments can be added, as well as these nodes are building blocks for more complex spatial structures like ways, buildings, or other areas. A way is an ordered list of nodes resulting in polygons or lines, if the first node is the last or not. Then it might represent a building or a park for polygons, or a river or highway in the latter case.

Moreover, relations describe situations like a bus route consisting of more than one way. Throughout this article, we focus on nodes and ways. According to this fundamental data model, any object might carry more information than its geographical position. There are labels such as "highway" or "amenity" available or opening hours for shops. With these classifications at hand, one could extract suitable data for a plethora of spatial use cases.

A remark on data quality: a large, open community is collecting data. This community cannot be at any place at any time. Therefore, use this data carefully and think about the data critically. In general, infrastructure changes slowly, but it changes over time and space. Also social and commercial facts change and it is quite difficult to keep up with this pace. Keep that in mind whenever you work with OpenStreetMap data.

Getting started with overpy and folium


At the beginning, there is usually a python environment and some libraries one should use to explore, gather, and process data. Throughout this first paragraph, we use overpy for data extraction, and folium to visualize spatial data. A starting point might be choosing a correct bounding box as an object where to look for data. The secret sauce here is to find out the correct coordinates in a reasonable coordinate system. Here, we use latitude and longitude in the WGS84 notation having a rectangular bounding box including Berlin. We will revisit WGS84 later on and explain it in depth.

Please pay attention to the chosen area. It could cause fetching a huge amount of data if you do not choose this bounding box smart. My advice, use https://overpass-turbo.eu to pre-query and find out the right dimensions. This particular overpass query fetches way-objects from the given bounding box. The code snippet below also introduces a class MapConfig configuring folium map parameters.

After creating an API-query, there are functions necessary to execute it. Therefore, before putting all puzzle pieces together, we introduce functions called _fetch_highwaydata and _process_highwaydata. The first function returns an overpass API object combined with the given query in a particular bounding box. As usual in software design, one could argue which statements to pass and what is the most modular object. For different tasks, one could possibly pass also self-defined queries and OSM objects to get a more individual statement.

The second function processes the given raw data from the API and restructures them to dictionary data objects. The idea is to extract and split coordinates, nodes, and ways. As a next step we introduce a function that creates a folium map called _createmap. In general, a folium map object will be initialized by Map, passing a starting location, a certain zoom-factor and information about the underlying tiles. These have already been initialized in the MapConfig class above.

There are two ways of adding data to a map. Either you are simply adding data to the map-object m, what results in simply showing the data without having any options. Another way is to add data to different layers. With this technique you are able to toggle layers on and off, or hide these when mounting a map. The corresponding Layer Control can then be found in the upper right corner.

To configure the main flow of the program, we introduce a function called main to orchestrate all other functions. In addition, one can also add the constructing nodes as a layer. But, be aware of how your map will react in terms of response times. In January 2025 the given bounding box contained 55K highway entities and about 135K node entities.

network security, computer networks, data communication, wireless networking, LAN, WAN, VPN, network topology, routing protocols, cybersecurity, firewall protection, cloud networking, IoT connectivity, network infrastructure, bandwidth management, network monitoring, server configuration, IP addressing, network performance, digital communication

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