Databike Pilot Project

Have you ever wondered if you could sell the data you generate on an e-bike? Well, you'll find out in our Data Governance & Token Economic System Proof-of-Concept

Databike is a micro-mobility data governance and token economic system project that we are developing in Las Vegas, Nevada.

The project is spear-headed by Charles Adjovu, Director & Researcher at Ledgerback Commons Research Cooperative (LCRC).

We started working on the project in Summer 2019 and we feel that we have made enough progress on the research to warrant an individual post.

Research Motivation & Questions

Our research motivations for starting the Databike Pilot Project were:

  • the rapid growth of shared micro-mobility services in the United States during 2019 [2],

  • the lack of discussion on data stewardship and governance around user-generated micro-mobility data and how this applies generally to the platform & data economy,

  • the lack of blockchain and micro-mobility discussion and literature as a means of transportation innovation, and

  • general curiosity around how token economic systems could be applied to the micro-mobility industry.

Our current list of research questions include:

  1. Can we use blockchain as part of a micro-mobility solution?

  2. Can we create a token economic system to incentivize cyclists to generate micro-mobility data by riding e-bikes?

  3. Can we develop a new business model for micro-mobility data stewardship?

  4. Can we develop a new type of cooperative that combines a transportation network with data stewardship?

  5. If we can share micro-mobility data, then will a public-commons partnership (PCP) become a viable route of sustaining the Databike business model?

  6. Can we develop a marketplace for micro-mobility data exchange?

  7. Can we build a micro-mobility pilot (creating an e-bike with data storage and sharing capabilities) that can serve as a basis for implementing our token economic system?

  8. Can we generate large amounts of micro-mobility data with our token economic system such that machine learning and artificial intelligence methods would be usable for data analysis and prediction?

Methodology

Our methods for the Databike Pilot Project is two-fold.

First, we are developing a prototype e-bike by converting a mountain bicycle into an e-bike by adding the basic e-bike parts (motor, battery, brakes, etc.) to the mountain bicycle.

Second, we are developing a token economic system (and business model if need be) that is intended to incentivize the following behaviors:

  • the generation of micro-mobility data

  • the purchase of e-bikes

  • the healthy usage of e-bikes

  • the greater usage of e-bikes

Specifically, we will be working on a token generation algorithm for e-bike usage, and a business model to incentivize e-bike purchases and conversions.

Third, we will be developing a data exchange marketplace so that users and buyers have a place to sell and buy micro-mobility data (and avoiding many of the ethical concerns with obtaining this data).

Issues Addressed

Databike intends to address three primary issues in the micro-mobility ( sharing mobility, etc.) industry and the platform & data economy in general:

  1. Users of Micro-mobility platforms do not have any control over how mobility providers use, share, analyze, and store their data [1];

  2. Users of Micro-mobility platforms cannot store their micro-mobility data on their own private devices; and

  3. Users of Micro-mobility platforms cannot individually share their mobility data with third parties and receive remuneration for data exchange.

Databike intends to resolve the three (3) above issues by:

  1. Allowing users to store their mobility data on-premise and export to their own private device

  2. Allowing users to sell their mobility data to interested third parties in a safe and secure marketplace

  3. Allowing users to decide who, when, where, and why there data gets shared.

Desired Outcomes

The current desired outcomes of this pilot project are as follows:

  • Add to the minimal literature on blockchain and micro-mobility as a means of innovating transportation;

  • Add to the minimal literature on token economic systems;

  • Develop a data governance model, token economic system model and business model (“Models”) for securing and exchanging user-generated micro-mobility data

  • Raise the alarms on data governance in our token and data economies, and why we need to have an ongoing discussion on data governance before users lose any chance of having their voices heard; and

  • Offer the Models to existing bikesharing systems (with special benefits for cooperatives) and local governments.

Eventually, with all of the data produced, it should be possible for third parties to develop artificial intelligence and machine learning tools and models to understand mobility data regarding electric-assisted bicycles.

Current Stage

Currently, we are developing a prototype e-bike that can store micro-mobility data on-premise and share such data with a data exchange marketplace.

After the prototype is developed, we will move onto developing the token economic system and data exchange marketplace.

Future Steps

After the prototype is developed, we will move onto developing the token economic system and data exchange marketplace.

Get Involved

Send a message to hello@ledgerback.coop about your interest in joining our Databike team and how you would like to contribute to the pilot project.

You should hear back from us within 3 -4 business days.

Current team members

  • Charles Adjovu

  • Gavin Hansen

  • Manny Williams

References

[1] Booz Allen Hamilton, Mobility on Demand: Operational Concept Report 136, US Department of Transportation (USDOT): Office of the Assistant Secretary for Research and Technology Intelligent Transportation Systems Joint Program Office, https://rosap.ntl.bts.gov/view/dot/34258

[2] Article 4. The Electric Scooter Uprising, Amalgam Staff, https://medium.com/amalgam-ledgerback/article-5-the-electric-scooter-uprising-736e3c2ba065?source=friends_link&sk=c3bb54972b8e1665c4babba28961b6c4