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This brief article points both to the issue of the protection of personal data  that shared mobility operators licenced by cities generate AND to the limited value of these data to cities unless they are formated in a common fashion for integration across providers in a way that the city can generate information in a comprehensive fashion.

    by  Scott Shepard  –  20 Sept. 2019

Monetizing Data and Solutions in a Disruptive Shared Mobility Landscape

Monetization .This appears to be the holy grail of mobility nowadays. The use cases abound, and ideas are plenty. The problem is, many times providers of mobility solutions and platforms have “solutions looking for problems”.

Given the peak hype of “Smart Cities” in 2017–2018, the value of data appeared to be the glue that bound all applications together, whether it be IoT devices monitoring environmental conditions, to more questionable uses such as street surveillance by law enforcement, which brings protection of personal privacy into question.

However, now that CASE (Connected, Autonomous, Shared, and Electrified) mobility has matured over the past 2 years to a point when we are now seeing a rapid transformation of the urban landscape with the proliferation of micromobility, data (and its commercial monetization) is now seen as an essential ingredient in the success of such new options.

Specifically, many new digital platforms have been developed that “fetch” micromobility data (typically in MDS and GTFS formats) and bundle into intuitive dashboards which municipalities and public transport authorities (PTAs) can utilize to monitor and enforce mobility service providers (MSPs).

Data quality and accuracy is imperative for such new opportunities to succeed in the long term. Without insights that provide true locations of mobility options and place them into their proper geographic context, only a cursory value will be able to be extracted.

In order to enrich the environment that governments (and large corporates) require with regards to understanding the mobility patterns on a city scale, GDPR-compliant and anonymized historical and real time data can empower regulators (and data scientists) with the insights required to understand the full mobility picture — related to the distribution, trip patterns, and load balancing of micromobility providers and assets.

The Free2Move City Mobility API and City Shared Mobility Insights provides cities, corporates, and 3rd party developers with the tools and insights required to deliver shared mobility. We fill in the gaps in the shared mobility landscape and empower authorities and businesses to best offer and price the right options, in the right place, at the right time.

View original article at medium.com