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This Deliverable identifies and examines various legal issues that are relevant to the production of, access to, linking of and re-use of big data in the transport sector. Chapter 2 sets the scene and introduces the concept of big data, its particular characteristics, its possible use in the transport sector, the existing policy framework, and the identified legal issues. In Chapter 3, the authors examine the various identified legal issues and discuss the challenges and opportunities that may arise in this respect, coming up with notably the following findings: Privacy and data protection: Some concepts, principles and obligations under data protection law appear to be problematic for the uptake of big data. In particular, the broad definition of "personal data" and "processing", the qualification of the various actors involved as (joint-)controllers or processors, the core data protection principles, the need to identify a ground for processing, the requirement to conduct data protection impact assessments, the implementation of privacy by design and by default measures, the rights of data subjects, and the requirement to put in place adequate data transfer mechanisms seem difficult to reconcile with the concept of big data. (Cyber-)Security: The requirement to put in place security measures is imposed in various legislations at EU and national level, including key instruments like the GDPR and the NIS Directive. However, such legislative framework remains rather general and vague as to which specific measures are deemed appropriate. In order to comply with this requirement, organisations involved in big data analytics generally need to rely on security experts and take into account the evolving guiding documents published by authorities such as ENISA. Relying on certification mechanisms, seals, marks, and codes of conduct will enable companies complying with their legal obligations and demonstrate their compliance. Breach-related obligations: The various actors of the (big) data value chain need to implement ...

This Deliverable identifies and examines various societal and ethical issues that are relevant to the production of, access to, linking of and re-use of big data in the transport sector. Chapter 2, on the one hand, discusses the concept of big data, its particular characteristics, and its possible use in the transport sector. On the other hand, it delves into the interaction between ethical and social issues and the ways to integrate these into the existing policy framework. In Chapter 3, the authors examine the various identified ethical and social issues and discuss the challenges and opportunities that may arise in this respect, coming up with notably the following findings:  Trust: Although the research in trust has already become relatively mature, the huge amount and diversity of data and data sources provides lots of new opportunities but at the same time poses many challenges for online trust, notably in the context of transportation.  Surveillance: Considering the role of government agencies and their increasing requests of information to the private sector for public security purposes, it appears necessary to adopt specific rules to regulate the information flow, to define the rights over data and to ensure adequate enforcement.  Privacy (including transparency, consent and control): The advent of the GDPR has had a considerable impact in the domains of privacy, transparency, consent and control. This strengthened legal framework is likely to respond to several ethical issues and thus improve end users' trust in the use of personal data in a big data context.  Free will: Although big data-driven profiling practices can limit free will, a huge part of what we know about the world comes from data analysis. Careful and appropriate information analysis can open up plenty of chances and might reduce the limitations and problems for free will.  Personal data ownership: This Deliverable concludes that a claim of ownership by a data subject in its personal data would be hard to sustain. Nevertheless, in a ...

Big data applications in the transport sector have achieved national and EU-level interest as a driver for future economic growth and at the same time a source of concern, in terms of negative socio-economic impacts. This report reviews current policies implemented in the EU, its Member States and internationally, which support or restrict the (re-) use, linking of and sharing of data, in the context of big data techniques and in the transport sector. Also, the report illustrates in selected examples of transport-related private companies, the types of private sector policies that have been adopted or promoted. While there are not any distinctly big data policies, each political entity has implemented some policies aimed at protecting the privacy of its citizens, encouraging data sharing among private and public sector entities, and develop policies that support the digitalization of the transport sector. Some of the key areas of policy in the transport sector are for instance the implementation of Intelligent Transport System, the increased Open Data policies, Automated Driving, and Smart Mobility. Preceding and in light of these developments, the private sector has also moved ahead to incorporate the use of big data techniques into their own business models as process or product innovations. The potential applications in the transport sector are diverse, as digitalization is a major trend of the transport sector. The report covers six distinct transport sub-sectors, where the application of big data is or potentially could be used. The aim is to highlight the challenges and enablers of data sharing in the different cases. The cases are: Railway Operators, Open Data in the Airport Operator Context, Real-time Road Traffic Management, Big Data in Supply Chain Management, Managing Port operations, and Connected and Automated Vehicles. The development of a policy roadmap to foster the growth of big data in transport will require an understanding of how existing policies affect the economic, political, social and ...