Open source data mining infrastructure for exploring and analysing OpenStreetMap

• Verfasst von: Mocnik, Franz-Benjamin [VerfasserIn]
• Verfasst von: Mobasheri, Amin [VerfasserIn]
• Verfasst von: Zipf, Alexander [VerfasserIn]
• Titel: Open source data mining infrastructure for exploring and analysing OpenStreetMap
• Verf.angabe: Franz-Benjamin Mocnik, Amin Mobasheri and Alexander Zipf
• Fussnoten: Published: 28 May 2018 ; Gesehen am 15.06.2018
• Titel Quelle: Enthalten in: Open geospatial data, software and standards
• Jahr Quelle: 2018
• Band/Heft Quelle: 3(2018,1) Artikel-Nummer 7, 15 Seiten
• ISSN Quelle: 2363-7501
• DOI: doi:10.1186/s40965-018-0047-6
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1576406180
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

OpenStreetMap and other Volunteered Geographic Information datasets have been explored in the last years, with the aim of understanding how their meaning is rendered, of assessing their quality, and of understanding the community-driven process that creates and maintains the data. Research mostly focuses either on the data themselves while ignoring the social processes behind, or solely discusses the community-driven process without making sense of the data at a larger scale. A holistic understanding that takes these and other aspects into account is, however, seldom gained. This article describes a server infrastructure to collect and process data about different aspects of OpenStreetMap. The resulting data are offered publicly in a common container format, which fosters the simultaneous examination of different aspects with the aim of gaining a more holistic view and facilitates the results’ reproducibility. As an example of such uses, we discuss the project OSMvis. This project offers a number of visualizations, which use the datasets produced by the server infrastructure to explore and visually analyse different aspects of OpenStreetMap. While the server infrastructure can serve as a blueprint for similar endeavours, the created datasets are of interest themselves too.