Info

Wednesday, 01/12/2021

Thursday, 02/12/2021

18.00 - 20.00

via Zoom

9.00 - 18.00

via Gather

  • Welcome speech
  • Introduction
  • Presentation of the challenges by mentors
  • Assignment to challenges
  • Questions & Answers
  • Welcome speech
  • Hacking
  • Pitching of results to the audience

Make an impact at the Transnational Hackathon on Mobility on 01. / 02.December 2021!

As mobility is a big factor of climate change, you can help our DEAS project to find innovative ideas for mobility in the Alpine Space. All interested people are invited to work in teams with other participants to tackle the challenges of mobility! The event will take place online on Zoom and Gather.  You will receive an email with all the necessary links on November 29.


Challenges:​​​​​​​​​​​​​​

New urban sustainable future of mobility- Walkability & Bike & Shared Taxi – regional focus Austria, Graz: Use the available open data sets of Austria/Styria and Graz to identify new applications for a future urban mobility.​​​​​​​

Cross-border Tourism (CroBoTo) across the French-German Border by using Multimodal Mobility Services:  Develop a concept that meets all criteria to convince cross-border tourists to travel with publicly accessible mobility services instead of using their own car. 

MetaAPI & App 1.0: Currently, if someone wants to rent a bike or an e-scooter, he/she has to download many different apps. The goal is to develop one application for sustainable multimodal mobility (combining data from bike sharing, car sharing, e-scooter sharing, parking, public transport, etc.).

Moving Vercelli by bike (MoVeByBike): Share your idea with us and develop your solution based on Open Data. Create a new dataset to develop a suitable mobility solution and tell us what kind of data you need beyond the ones provided and already available on the web.

MaaS: Intermodal routing (with visualization) - going from Strasbourg to Linz via different modes of mobility: Develop a concept or prototype that meets all the requirements of transnational routes for occasional transport or tourism.

Sustainable transports within Veneto´s Alpine space: The challenge pivots around producing a structured and innovative idea for a decision support system (DSM) that can help municipalities and territorial administrators to create a more sustainable transport management system. This could be achieved either through services that recommend time interventions or through services that help design better solutions for the future.

Digital Twin: Providing technical information and raising awareness of the digital twin. Collecting potential applications for a digital twin. Develop traffic modeling in the Constance digital twin. Develop a conceptual document that can be used as a blueprint and guide for implementing a digital twin.

Secure Spontaneous Ridesharing: Improve mobility in rural areas through safe and spontaneous ridesharing at ridesharing stops (e.g., bus stops, ridesharing benches). These open ridesharing systems should be measurable and safe.​​​​​​​

Smart electricity using for your private vehicles at home (car, e-bike, scooter) ​​​​​​​

... and more - it is up to you!


Who is behind it?

The Hackathon is a joined effort from DEAS (Exploiting Open Data to strengthen Alpine Space competitiveness).  It is transnational - the participants will be from Austria, France, Italy, Slovenia and Germany.The partners are: Bwcon GmbH (DE)City of Constance (DE)City of Vercelli (IT)CSI - Piemonte (IT)Veneto Region (IT)CCIAA TB (IT)Grand E-Nov (FR)Lyon Urban Data LUBA (FR)Styrian Business Promotion Agency SFG (AT)Business Upper AustriaBusiness Upper Austria BIZ-UP (AT)Technology Park LjublJanaLtd (SI)City of Ljubljana (SI).


Our Open Data:

One reason we are organizing the hackathon is to leverage the value of open data. That is why the challenges will be tackled with the help of open data. Here you can find possible data sets:  Veneto, Slovenia, Constance & Baden-Württemberg, France (and Lyon), Piedmont, Austria (with access to Linz, Graz & Vienna). 

In addition, there will be datasets provided by our mentors.