Data Management of Heterogeneous Bicycle Infrastructure Data

Johannes Schering (), Pascal Säfken, Jorge Marx Gómez, Kathrin Krienke and Peter Gwiasda
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Johannes Schering: Carl von Ossietzky Universität Oldenburg
Pascal Säfken: Carl von Ossietzky Universität Oldenburg
Jorge Marx Gómez: Carl von Ossietzky Universität Oldenburg
Kathrin Krienke: Planungsbüro VIA eG
Peter Gwiasda: Planungsbüro VIA eG

A chapter in Advances and New Trends in Environmental Informatics 2023, 2024, pp 219-236 from Springer

Abstract: Abstract Data that is related to traffic and specially to cycling is already commonly used in bicycle infrastructure planning processes. Data supports the understanding of bicycle use. What becomes more relevant is data about the state of the bike infrastructure. In general, cycling data sources have become increasingly heterogeneous what increases the need for suitable data management. This contribution presents the data management solution of the INFRASense research project that aims at the quality assessment of bicycle infrastructure. As a first step, the state of the art of data applications in cycling planning is presented. The data pipeline of the research project that considers many of these data sources is based on a Data Lake approach where the raw data sets are stored before transforming these individually for further data processing. The available data sources can be divided between time series and non-times series data. The related data models that allow the combination of different tables inside the database will be presented. As a last step, the contribution gives an outlook to forthcoming applications that will build up on the presented data management solution (interactive dashboard for data analysis).

Keywords: Cycling infrastructure data; Time series data; Non time series data; Snowflake schema; Object-relational data model; ETL; Shapefiles; Data Lake (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-46902-2_12

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