Increasing Data Availability for Transportation and Logistics

In the field of mobility research, up-to-date data are needed in order to explore current problems and challenges. Proponents of Open Science argue that research data should be Findable, Accessible, Interoperable, and Reusable (FAIR). Adopting the Design Science Research methodology, we derive design requirements, design principles and design features for a suitable platform to realize the FAIR principles, based on a literature review, existing solutions, and interviews with mobility researchers (with qualitative and quantitative research backgrounds). In a practical way, and after an evaluation of our prototype, we show how a platform should be designed to allow users, regardless of their level of experience, to participate. We contribute to the discussion in the field of Open Science on how artifacts should be designed according to an open design, which also takes into account the different needs of researchers.

The COVID-19 pandemic marked a global disruption of unprecedented scale which was closely associated with human mobility. Since mobility acts as a facilitator for spreading the virus, individuals were forced to reconsider their respective behaviors. Despite numerous studies having detected behavioral changes during the first lockdown period (spring 2020), there is a lack of longitudinal perspectives that can provide insights into the intra-pandemic dynamics and potential long-term effects. This article investigates COVID-19-induced mobility-behavioral transformations by analyzing travel patterns of Berlin residents during a 20-month pandemic period and comparing them to the pre-pandemic situation. Based on quantitative analysis of almost 800,000 recorded trips, our longitudinal examination revealed individuals having reduced average monthly travel distances by ∼20%, trip frequencies by ∼11%, and having switched to individual modes. Public transportation has suffered a continual regression, with trip frequencies experiencing a relative long-term reduction of ∼50%, and a respective decrease of traveled distances by ∼43%. In contrast, the bicycle (rather than the car) was the central beneficiary, indicated by bicycle-related trip frequencies experiencing a relative long-term increase of ∼53%, and travel distances increasing by ∼117%. Comparing behavioral responses to three pandemic waves, our analysis revealed each wave to have created unique response patterns, which show a gradual softening of individuals’ mobility related self-restrictions. Our findings contribute to retracing and quantifying individuals’ changing mobility behaviors induced by the pandemic, and to detecting possible long-term effects that may constitute a “new normal” of an entirely altered urban mobility landscape.