weeklyOSM-stats: Analysis of the weeklyOSM profile over the last ten years with PostgreSQL

STATE OF THE MAP 2025 Manila, Philippines. October 3th to 5th, 2025 weeklyOSM-stats: Analysis of the weeklyOSM profile over the last ten years with PostgreSQL Raquel Dezidério Souto Virtual Institute for Sustainable Development - IVIDES.org™ and IVIDES DATA™ Rio de Janeiro, Brazil. [email protected] The OpenStreetMap (OSM) ecosystem is very vast, making it complicated to investigate user preferences for OSM-related software or topics. This ecosystem has an important community component and a large set of software resources that serve many different purposes, such as retrieving, editing, validating or converting data, collecting data in the field, routing, geoservices, etc. These programs are increasingly present in the daily lives of OSM users, especially in countries outside the US-Europe axis (such as Latin America and Africa), where new users are becoming interested in OSM and the applications, which is reflected in the significant increase in the number of contributions on the map. This research aims to survey the publication profile of the weeklyOSM [1], analyzing the content of the issues published on the last ten years (numbers 272 to 768), since it began to be organized with the OpenStreetMap Blog Collector [2], a system with free and open source code, designed, programmed and improved by TheFive [3] and which has been used to manage the content of the weeklyOSM since its number 272, in September 2015. The weeklyOSM reports news from the reporting week, is produced by mappers and OSM enthusiasts and is independent from organizations and companies [4]. It covers currently 15 languages and has been informing the OSM user community without fail since its release as the German weekly OSM-Wochennotiz [5], whose initial issue was published on July 23, 2010. Its workflow naturally favors sampling OSM-related topics from a wide variety of sources, such as social networks, blogs, OpenStreetMap Foundation channels or institutional news sites. Thus, by analyzing their content, it is hoped that the results will serve as a proxy for understanding the interest in certain categories and the usage of certain software by OSM users. The methodological flow started with the initial export of the articles stored in the OSM Blog Collector (OSMBC), in a file in the comma-separated values (.CSV) format. The records were then imported into a PostgreSQL database and analyzed using Structured Query Language (SQL). Of the initial 32,261 records (articles) and 35 categories, the records prior to number 272 were excluded and the categories were standardized to conform to the actual weeklyOSM's categories: About us, Breaking news, Community, Did you know that..., Education, Events, Humanitarian OSM, Imports, Licenses, Local chapter news, Mapping, Mapping campaigns, Maps, Open Data, OpenStreetMap Foundation, OSM in action, OSM in the media, OSM research, Other Geo Things, Picture, Programming, Releases, Software, Upcoming Events. Thus, after the initial processing, 18,672 records (articles) were obtained, classified into the current 24 categories and considered as the initial set for the analysis. In a second stage, queries were made regarding the occurrence of 102 software in the articles (e.g. “Panoramax”), saving the results files in .CSV format and making them available on GitHub [6], with its subsequent classification into 14 software groups: 3D model, aerial imagery, API, converter, data extraction, data quality, desktop editor, library, mobile editor, notes editor, OSM based service, routing, street level imagery, tagging, and re-importing them into the database in a new table, forming a second set of records. Making the data and results available on GitHub guarantees the transparency and reproducibility of the analysis. The search for software and the design of the categories were inspired by the sources [7-11]. From the starting set for the analysis, the initial and final numbers of the category (e.g. “Mapping”) were collected, and the total number of articles in the category was calculated, resulting in a ranking showing the most popular categories for publishing articles. From the second set (only the records of the 102 selected software), the software's indices were calculated, which correspond to the software's participation in the group to which it belongs. The results found in the first stage of the analysis show that the ten most popular weeklyOSM categories to associate with articles were: “Mapping” (2,778 articles), “Other geo things” (2,331), "Community" (2,212), “Did you know that...” (1,177), “Events” (1,153), “Maps” (1,064), “Software” (1,060), "Programming" (963), “Humanitarian OSM” (821) and “OpenStreetMap Foundation” (782); and the full ranking can be accessed on the GitHub [12]. In the second stage of the analysis, with the set of data which contains only the records of articles that included the 102 selected software, two main statistics were obtained: i) the number of articles for the 14 groups of software and ii) the participation index of a given software in the group to which it belongs. For the first processing (i), the five groups with the highest number of articles were: “Desktop editor” (1,193), “OSM based service” (968), "Routing" (524), “Mobile editor” (522) and “Street Level Imagery” (424), and the full results are found on the GitHub [13]. For the second processing (ii), there was a greater variety of software in the “OSM based service”, “Desktop editor” and “Mobile editor” groups. The complete set of graphs are found on the GitHub [14]. As a result of the research, we could infer that weeklyOSM, over the last ten years, has expressed the variety of themes and programs related to OSM, with a large representation of content pertinent to “mapping” and “community”, which are at the heart of the OSM ecosystem. Thus, could be inferred that the analysis had a representative result from the point of view of reality; and c) in addition to this “panoramic” view of the content in general, it was possible to observe the participation of the software in their respective group, inferring their relevance in the context of the collaborative mapping with OSM. Limitations of the research include the difficulty in performing queries on very heterogeneous strings, requiring greater attention from the researcher and the static nature of the analysis, making it more time-consuming to carry out the workflow. With the publication of this research, we hope to highlight the wide variety of information resources available to OSM contributors and, in particular, to highlight the role of weeklyOSM as a representative vehicle for information on the OSM ecosystem, freely accessible to the community and which has fulfilled its objective without fail since its first edition on 2010. The author would like to thank her fellow editors who took part in the research: TheFive (raw data), Strubbl and MatthiasMatthias (program classification review) and Manfred Reiter (historical information and final review). Thanks also to barefootstache for proofreading this English abstract, and to all the weeklyOSM contributors. [1] weeklyOSM Editorial Team. weeklyOSM. https://weeklyosm.eu [2] weeklyOSM Editorial Team. OSM Blog. https://blog.openstreetmap.de/blog/2010/07/osm-wochennotiz-nr-1/ [3] TheFive et al. OSM Blog Collector. https://osmbc.openstreetmap.de/ [4] weeklyOSM Editorial Team. Blog OSM Histoire. https://blog.openstreetmap.de/mitmachen/ [5] TheFive. TheFive's OpenStreetMap user profile. https://www.osm.org/user/TheFive [6] Souto, R. D. weeklyOSM-stats. https://github.com/raqueldeziderio/weeklyOSM-stats [7] Comparison of editors. OpenStreetMap Wiki. https://wiki.open streetmap.org/wiki/Comparison_of_editors [8] ToastHawaii. OSM APPs Catalog. https://osm-apps.org/?category=edit ("Improve the map" category) [9] OpenStreetMap contributors. List of OSM based services. OpenStreetMap Wiki. https://wiki.openstreetmap.org/wiki/List_of_OSM-based_services [10] https://software.wambachers-osm.website/ [11] Editor usage stats. OpenStreetMap Wiki. https://wiki.openstreetmap.org/wiki/Editor_usage_stats [12] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/statistics [13] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/selection [14] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/graphics_software_in_group How to reference: SOUTO, Raquel Dezidério. weeklyOSM-stats: Analysis of the weeklyOSM profile over the last ten years with PostgreSQL. In: State of the Map 2025, Manila, Philippines, 3-5 oct. 2025. IVIDES DATA, Rio de Janeiro, 2025. DOI: https://doi.org/10.5281/zenodo.17298633. License: Creative Commons Attribution Share Alike 4.0 International (CC BY-SA 4.0) https://creativecommons.org/licenses/by-sa/4.0/legalcode