4th LeMO Project Meeting held in The Netherlands on 26-27 November 2018

The forth LeMO project meeting was held in Zoetermeer (The Netherlands) on the 26th and 27th of November 2019. All partners gathered to discuss the advancement of the project and the tasks ahead.

The day started with a welcome note by the host (Panteia) and a presentation of the project progress so far by the coordinator (WNRI) and continued with a presentation of the main WP2 achievements by respective Task leaders.

The coordinator of the NOESIS project (Ortelio) also attended the meeting and presented the NOESIS project and its ongoing work on Big Data in Transport Library. Opportunities for collaboration between the two projects were further discussed.

After the end of a very fruitful discussion on dissemination activities LeMO consortium discussed the results of the first year dissemination and the plan for next steps. First LeMO webinar planned for February 2019. The partners discussed the tentative agenda for the webinar and agreed on inviting NOESIS and two Case Study providers for short presentation in the webinar.

The second day of the meeting focused on a discussion on case studies in WP3. All partners discussed the progress of the running work package (WP3) and presented their plan for the case studies and related interviews that are about to begin in January 2019.

Deliverable 2.4 on Trade-Off from the Use of Big Data in Transport

In this report different types of rebound effects are addressed. This encompasses direct and indirect rebound effects, as well as society-wide, or overall rebound effects. Further different application areas of rebound effects are presented. They cover rebound effects in connection with energy efficiency measures and climate gas reduction measures, as well as in connection with measures aimed to reduce other environmental pollutants. Critique of the rebound effects is also presented. We then turn to strategies to mitigate the rebound effect and suggest approaches for assessment of rebound effects from the use of big data in transport. Two very different approaches are presented, that either focus on 1) the ICT-infrastructure or 2) the transport system. The two approaches are addressed in the two following chapters, first in the analysis of rebound effects from ICT and cloud computing (Chapter 5), then in connection with the LeMO case studies (Chapter 6). Passenger transport and freight transport are dealt with separately, also in connection with the various transport modes: road, rail, water and urban transport. The purpose of the chapter 7 is to map the aspects that may be relevant for further research in LeMO case studies and may be further elaborated in the next project phase in a report with consolidated case study findings.

A member of the LeMO team attended the NOESIS project meeting

On 13 November 2018, a member of the LeMO project team, Maruša BENKIC, attended a project meeting of its sister-project, on Big Data under the Horizon 2020 programme, NOESIS. The meeting was held at the premises of the JRC in Seville.

NOESIS meeting (Photo credit: NOESIS project)

NOESIS meeting (Photo credit: NOESIS project)

NOESIS (Novel Decision Support tool for Evaluating Strategic Big Data investments in Transport and Intelligent Mobility Services) aims at improving understanding about the impact of big data, with the final goal to develop a Decision Support tool which will be able to assess the potential of big data investments in transport. The project has been developing the Big Data in Transport Library (BDTL), the first collection of Big Data use cases in Transport.

The meeting started with a presentation of the NOESIS project by the coordinator (Ortelio) and continued with the overview of the main achievements so far. The NOESIS consortium was informed about the progress of LeMO and the deliverables produced so far. During the very successful and fruitful meeting, the teams discussed possibilities for synergies between the two projects and identified concrete opportunities to share the research outcomes and combine their efforts in effectively disseminating the project results.

LeMO co-organised workshop on "Policy issues, opportunities and barriers in big data-driven transport" at EBDVF 2018.

LeMO project has co-organised a workshop on "Policy issues, opportunities and barriers in big data-driven transport" at EBDVF 2018. The workshop was organised in cooperation with the BDVA Mobility & Logistics Subgroup & the TransformingTransport project on 14 November at Siemens Conference Center, Vienna. Considering the objectives of the LeMO and TransformingTransport projects, the interaction with industry experts is fundamental to challenge and validate the findings.

LeMO Coordinator, Rajendra Akerkar (WNRI) presented an overview of the LeMO project and described progress so far. Tharsis Teoh (Panteia) presented an analysis of the economic and political issues that are relevant to big data in transport. Further, Jasmien César (Bird & Bird) and Tharsis Teoh (Panteia ) reviewed policies supporting or restricting the (re‐) use, linking of and sharing of data in the transport sector. They described the work done on public and private policy issues in the first phase of the project. Jasmien César (Bird & Bird) also presented an analysis of various legal issues relevant to utilisation of big data in managing transport operations.

Adrián Irala Briones (INDRA) presented TransformingTransport project and big data challenges in the transport sector.

Akrivi Vivian Kiousi (INTRASOFT, TT) gave a brief summary of examples / Policy contribution topics highlighted by TransformingTransport Lighthouse project.

We invited representatives from key running Horizon 2020 projects in order to attempt to ensure cooperation and collaboration for a policy roadmapping activity. The following projects participated in the session:

  • Track and Know (Big Data for Mobility Tracking) - Dr Ibad Kureshi (INLECOM)

  • BigData Ocean (Maritime) - Dr Michele Osella (NTUA)

  • ICARUS (Aviation) - Dr Fenareti Lampathaki (SUITE5)

  • AEGIS (Public Safety and Personal Security) - Mr Perkakis (UBI) TBD

  • QROWD (Innovative Solutions to improve mobility and reduce traffic congestion) - Dr Luis-Daniel Ibáñez (SOTON)

  • CERTH (Results of Smart Mobility Living Lab providing cooperative services to passengers and freight respectively). - Josep Maria Salanova (CERTH)

We further reached out to the audience to gather valuable feedback that aims in the formation of a policy roadmap relating to the topics identified for big data in transport.

Ultimately, the results of the workshop, as fed by experts (including attendees of EBDVF 2018), will enable the identification of industry-led recommendations to (EU) policymakers in relation to big data, with a focus on the transport sector driving a roadmap creation activity to be fed by big data specialists and to validate, clarify, complement and/or challenge the identified opportunities, barriers and limitation to exploit big data.

Mrs Akrivi Vivian Kiousi of TransformingTransport project played a role of moderator in this workshop.

LeMO Researchers have published in-depth insights on legal issues that are relevant to the production of, access to, linking of and re-use of big data in the transport sector.

A new report published by LeMO project throws light on various legal issues that are currently relevant to big data in transport. This report 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. The report further 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.
Moreover, the LeMO researchers 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 measures, procedures and policies to abide by the strict notification requirements and be prepared to provide the necessary information to the authorities, within the imposed deadlines. Such requirements will also need to be adequately reflected in the various contracts between the stakeholders involved in the chain in order to adequately address any incident that may occur.

  • Anonymisation / pseudonymisation: Anonymisation and pseudonymisation techniques generally provide fertile ground for opportunities with respect to big data applications, including in the transport sector. Nevertheless, a balance will need to be struck between, on the one hand, the aspired level of anonymisation (and its legal consequences) and, on the other hand, the desired level of predictability and utility of the big data analytics.

  • Supply of digital content and services (personal data as counter-performance): Personal data as a form of payment for the supply of digital content is an emerging reality. In this respect, the proposed EU legal framework on the supply of digital content and services will ensure an adequate level of protection for the consumer. Nevertheless, the obligations concerning data may make some current digital services inoperable. Some companies may also start to charge for digital content services that are currently free. On a wider scale the ecosystem of innovative services in the field of transport could be jeopardised.

  • Free flow of data: The free flow of data presents a scenario in which no legal barriers hinder the cross-border flow of data. Such cross-border data flows may be restricted by data localisation requirements, which come in many shapes and forms. The new EU Free Flow Regulation should ensure the free flow of data across EU Member States, ensure data availability for regulatory control by EU authorities, and encourage the creation of codes of conduct for cloud services. The elimination of data localisation requirements is expected to create more innovation, which will positively impact big data analytics in the transport sector.

  • Intellectual property in big data environment: All intellectual property rights examined may have, to some extent, an impact on the use of big data, including in the transport sector. Depending on the manner in which and the extent with which a right holder may exercise its exclusive rights attached to the intellectual property right concerned, intellectual property rights may pose a barrier to data access, interoperability, and exploitation.

  • Open data: The EU institutions have taken both legislative and non-legislative measures to encourage the uptake of open data, most notably through the PSI Directive which attempts to remove barriers to the re-use of public sector information throughout the EU. Open data is a key component of most big data applications. A proposal for a revision of the PSI Directive intends to extend the scope of application to public undertakings, including actors in the transport sector such as ports and airports, public passenger transport services by rail and by road, and air carriers and EU ship owners fulfilling public service obligations.

  • Sharing obligations: While private companies often generate huge amounts of data, they are not always prepared to voluntarily share this data outside the company. This is due to the large number of legal, commercial and technical challenges associated with private sector data sharing. In certain circumstances, private companies are therefore legally required to share their data. This Deliverable succinctly examines the body of legislation specific to the transport sector that could impact a company's control of, the access to, or the rights in data. The analysis has shown that data sharing obligations are increasingly adopted in the context of Intelligent Transport Systems.

  • Data ownership: In a big data context, different third-party entities may try to claim ownership in (parts of) a dataset, which may hinder the production of, access to, linking and re-use of big data, including in the transport sector. This Deliverable demonstrates however that the current legal framework relating to data ownership is not satisfactory. No specific ownership right subsists in data and the existing data-related rights do not respond sufficiently or adequately to the needs of the actors in the data value cycle. Up until today, the only imaginable solution is capturing the possible relationships between the various actors in contractual arrangements, i.e. data sharing agreements.

  • Data sharing agreements: It is unclear whether the common practice to use data sharing agreements to govern the access to and/or exchange of data between stakeholders in a big data analytics lifecycle enables covering all possible situations with the necessary and satisfactory legal certainty. Data sharing agreements entail numerous limitations in the absence of a comprehensive legal framework regulating numerous rights (e.g. ownership, access or exploitation rights) attached to data, the way in which such rights can be exercised, and by whom.

  • Liability: The EU institutions have looked into and continue to examine issues related to extra-contractual liability, statutory liability, and safety requirements in the context of disruptive technologies, including in the transport sector. Based on their continued efforts, it will be possible to determine whether any regulatory intervention is required. The contractual liability legal framework, which differs across the EU, may however limit the uptake of new technologies, including big data in the transport sector. The present Deliverable further looks into the relevance for big data in the transport sector of the exemption of liability for intermediaries (the so-called safe harbour regime), and the proposed liability regime for suppliers of digital content and services under the Draft Directive on the Supply of Digital Content.

  • Competition: Assessing the market conduct of companies with access to large volumes of data raises complex issues under competition law. The difficulty of the exercise is compounded by the fact that the analysis also needs to take into account data privacy and consumer protection issues that are intimately linked to the questions under competition law. The present Deliverable considers three main areas in which competition law may have an impact on the use of big data. In view of the important role of big data in the transport sector, the Deliverable discusses the competition law issues that could arise with respect to organisations belonging to the broadly-defined "transport sector".

Finally, the report proposes possible ways of moving forward to encourage the production of, access to, linking of and re-use of big data in the transport sector, with a particular focus on the EU. The several improvements suggested by this Deliverable vary between the different legal issues and range from avoiding restrictive interpretations by the relevant authorities or courts, over soft law measures (such as guidelines and codes of conduct), to regulatory intervention at EU level.

For detailed report, please see: