Mobility Data

Open Online Data Meetup - Vol. 6

Mobility Data

Open Online Data Meetup - Vol. 6

When: 2020-12-02

Language: english

Registration: Here

Join the 6th Open Online Data Meetup to hear from our four speakers how they work with mobility data to make a positive change in society.

The event

With a pandemic, lockdowns and travel restrictions, many would not associate mobility with the year 2020. Still, researching the various aspects of mobility (social, environmental, …) remains important, not least because of the climate crisis.

This is why, for the last Open Online Data Meetup of 2020, we want to have a closer look at mobility data. Our speakers Pia, Mark, Jasmin and Marcus will share stories from their work: from academic research on the effects of electric mobility on power grids to developing infrastructure to collect mobility data in a German city to looking at bike sharing data to working with the WHO in “data-poor” areas.

Approximate agenda (subject to changes):

  • 19:00-19:05: Welcome by host Frie
  • 19:05-19:25: Equality in mobility solutions for a world in which data are far from equal (Mark Padgham)
  • 19:25-19:35: Measurig Air Quality and Counting Vehicles in a German city (Pia Baronetzky)
  • 19:35-19:55: Using Mobility Data to Simulate the Impact and Opportunities of Electric Vehicles in the Smart Grid (Marcus Voß)
  • 19:55-20:15: tba (Jasmin Classen)
  • 20:15-20:30: Q&A and Discussion

The talks

Equality in mobility solutions for a world in which data are far from equal

The world is full of innovative approaches to transforming urban mobility into more sustainable, environmentally, and socially beneficial forms, yet many proposed “solutions” are derived by organisations based in the global north, and presume amounts of types of data typical of their own cities, preventing them from ever being globally effective. I’ll briefly outline a few lessons learnt from working with the WHO to develop mobility solutions for cities well beyond the global north, and which no not have anything like the kinds of data presumed necessary for insightful mobility analyses. Most importantly, I’ll hope to convince others of the importance of developing mobility solutions which are simple, robust, generalisable, transferrable, and ultimately more effective.

About Mark:

Mark is a Software Research Scientist for rOpenSci, an orginisation dedicated to “Transforming science through open data and software,” and for which he is helping to develop a new system for peer reviewing statistical software. He also develops R packages for accessing and analysing open spatial data, with a particular focus on urban planning and transport. He is a founding member of Active Transport Futures, and the lead developer of moveability.city, a platform for open-source, open-access interactive visualisations of urban moveability.

Measurig Air Quality and Counting Vehicles in a German city

Pia will talk about her student job where she helps a German city to build infrastructure to count vehicles like cars and bikes. With measuring air pollution at the same time, this makes it easier to act when necessary and to observe potential increases of the amount of bikers.

About Pia:

Pia studies Mathematics at the Technical University of Munich. She also works at Hawa Dawa as a Data Science working student, helping to count vehicles and measure air quality.

Using Mobility Data to Simulate the Impact and Opportunities of Electric Vehicles in the Smart Grid

This talk touches on how we have used different open, not-so-open, open-but-impractical, and scraped mobility data to model expected electric vehicle charging scenarios. These are input to our Electric Vehicle Infrastructure Simulator (ELVIS - prepare for a logo including a car with a quiff!) that generates electric power demand time-series from mobility data for usage within different simulation studies. For instance, these can model the impact of electric vehicles on the electric power grid, but also the opportunities of exploiting their mostly parked batteries for using more locally produced renewable energies. The work has been done within different research projects, namely FlexNet4E-Mobility, Neue Berliner Luft, Hackathons within research project WindNODE, and studies for Berlin’s local system operator Stromnetz Berlin.

About Marcus:

Marcus is a Ph.D. student working in data analysis of smart meter data with applications in forecasting and clustering. He leads the working group Smart Energy Systems of the DAI-Lab at the TU Berlin that researches how AI, Machine Learning, and data-driven approaches can support the energy transition and digitization of the energy system.

Analyzing bike sharing demand and its driving factors in Hamburg with R

For a bikesharing system to be successful, reliable availability of bikes and well-placed stations are key. This can only be achieved if the demand for shared bikes across a city is known. The amount of available open data about bikeshare usage has grown in the last years which offers many possibilities to analyze said demands. In a seminar paper for computational social science I therefore used data about “Call A Bike Hamburg” published by Deutsche Bahn AG to evaluate different factors driving trips across the city. I’ll give an overview over how to prepare bike trip data for analysis, what model to use for predictions and how to use openstreetmap to create interesting features like intersections or points of interest within a certain area or shortest routes between coordinates. My goal is to show you the potential that bikesharing data has and fun ways to work with spatial data in R.

About Jasmin: Jasmin studies in the Master’s program Social and Economic Data Science at the University of Konstanz, after a Bachelor’s degree in Sociology. She is a member of CorrelAid since its Meetup in 2017 and takes care of Education & Knowledge Management at CorrelAid. She also hosts our podcast “CorrelTalk – the CorrelAid Podcast”.

Registration

Please register on Eventbrite. Once you’ve registered, you’ll find the Zoom link there.

The Open Online Data Meetup

The Open Online Data Meetup (OODM) is an online-based meetup series which provides the space to share interesting insights and entertaining stories from the field of data science with other people from the community. OODM is organized by the CorrelAid Education Team together with CorrelAidX Bremen. If you’re interested in speaking at the OODM, please write an email to the organizing team.