Specific Challenge: A massive amount of data is already produced by
the transport system and the trend is set to continue at an increasing pace.
Optimal use of the available data is indispensable in order to advance towards
an intelligent transport system that reduces congestion, environmental impact
and increases safety. On
the basic level, the challenge lies in ensuring that e.g. manufacturers,
operators, or authorities can properly take advantage of the data produced for
the improvement of their operations and services. Access to, reuse and storage
of data is not only important for private companies active in the transport
industry (business-to-business or B2B), but also for the public sector
(business-to-government or B2G) for a more evidence-based decision making and a
better public service delivery, such as transport safety or reduction of
pollution from all transport modes.
It is of key importance to develop a clear understanding of the areas where data exchange and digitalisation are required for improved system effectiveness. In these areas, data to be used in transport models need to be defined and harmonised.
On a more advanced level, in order to provide connectivity across the various components of the multimodal transport system, enable innovation and emergence of new business models, we need solutions for safe and secure collection, storage and sharing of transport data (both operational and research) across various actors and different transport modes.
based solutions could provide a high level of integration and accessibility of
transportation data across the system and be used for variety of purposes,
including research, development and innovation. However a number of challenges
will have to be tackled before a successful wide scale implementation of cloud
solutions for transport can take place, such as data privacy and security,
standardisation and competitiveness issues, data interoperability and
accessibility, governance, etc.