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Deliverable 3.2 Case study reports on constructive findings on the prerequisites of successful big data implementation in the transport sector

The deliverable presents seven reports of the case studies conducted in Work Package 3 during Task 3.2. The case studies conducted are the following:

• Case study 1 “Railway transport”

• Case study 2 “Open data and the transport sector”

• Case study 3 “Real-time traffic management”

• Case study 4 “Logistics and consumer preferences”

• Case study 5 “Smart inland shipping”

• Case study 6 “Optimised transport & improved customer service”

• Case study 7 “Big data and intelligent transport systems”

The methodology outlined in D3.1 “Case study methodology” was used as a template for each of the case studies. The template provided a consistent, but flexible approach to address the unique circumstances and learnings in each case study. It also leveraged the case study leaders’ strengths in understanding the applications of big data technology in transport operations.

Besides developing a deep understanding of the big data technology and its business applications, the case studies also present an analysis of the issues that serve as ‘opportunities’ and ‘barriers’ to the implementation of big data, as well as the resulting outcomes of the implementation. These issues were analysed using the knowledge developed in Work Packages 1 and 2 of the LeMO project, from economic, political, social and ethical, legal, and environmental perspectives.

The LeMO project's interim review in Brussels

On Wednesday, 26 June 2019 the LeMO project team travelled to Brussels for the 1st interim period review meeting by the INEA & EC. The team presented in detail the work done so far, demonstrating results, facts and achievements as these have occurred during the first 18 months lifetime.

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The agenda for the day was full as a broad range of topics needed to be covered in the space of six hours. The Coordinator and Work Package Leaders gave concise presentations on key achievements made, potential challenges faced and next steps of each work package. The Project Officer provided comments after each presentation. Once the series of presentations was over the progress and main results had been discussed.

The first impression of the team after the review completion was that of satisfaction and recognition of the excellent work done so far, of course with some constructive feedback. The commitment of the different partners all along the project half-life, but also during the review preparation was excellent, leading to important achievements, and a comprehensive defense of them in front of the Project Officer. It was very successful meeting and a good opportunity to get feedback from the project officer.

It is with enthusiasm that the Partners have embarked on the second half of the project and are now busy preparing for the trend analysis and road-mapping set to start this summer.

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.