Data sharing
Data is the water feeding the growth of Mobility as a Service. It needs to be treated with care, as a common resource providing life to the mobility ecosystem. We may need to work a bit to shed some industrial metaphors that have become entrenched in the way we describe data, so that we can be open to emerging possibilities through a culture of sharing and stewardship.
There are several types of data on which to build a resilient MaaS ecosystem. This chapter will describe a couple of more common data sets and give some insight as to how we can share.
Origin-destination data
User journies, from a MaaS perspective, typically start somewhere and end somewhere else. These 'somewheres' can be described in terms of space, or place, and time. For example, a person may go from a city center (origin) to a recreation area on the outskirts of the city (destination) on a Friday evening (time).
When we start to collect origin/destination/time data for many journies, a picture starts to emerge, often resembling a 'heartbeat of the city' a flow of people through common corridors. These data and their representative 'pictures' can be used for many purposes, including urban planning or even scheduling an individual trip to avoid congesiton.
Real-time transportation network data
Increasingly, road vehicles and mobility applications are able to provide data about their movement and surroundings. These data can be used to paint a picture of the current situation across a network. In turn, this picture can be used to optimize the transportation network, reducing bottlenecks and even avoiding accidents.
Promoting a culture of data sharing
Sharing data makes it possible to achieve greater accomplishments than if we work alone. It is a win-win situation, in that new data can supplement and amplify other data sets. This unlocks new markets and increases the potential of society as a whole.
With those aspirations, how do we take practical steps foward and establish data sharing policies in our own organizations? Luckily, there are a whole lot of people pooling their skills and collective wisdom to promote the open data movement. One key strategy is to start small and take incremental steps. We can also align with existing efforts for data sharing, adopting technologies and best practices of thos who have proceeded us.
Further reading
Open Data
- Community Data License Agreement
- International Open Data Conference
- Project Open Data: Implementation Guide
Open Transport Data
- OpenTraffic - global data platform to process anonymous positions of vehicles and smartphones into real-time and historical traffic statistics
- oneTRANSPORT - open marketplace for data
- OpenTransportNet - brings together open geo-spatial data within City Data Hubs and enables it to be viewed in easy-to-understand ways
- SharedStreets - a shared language for the world's streets
Origin-destination data/visualization
- Visualize flows with FlowMapper
- Small multiples for OD flow maps using virtual layers
- Service Areas, Traffic and QGIS