The H2020 LeMO project webinar took place on 27th February 2019. You can find the presentations on our YouTube channel:
The third newsletter of the LeMO is now published online. It describes some of the achievements of the project so far. It can be downloaded from the link below.
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.
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.
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 (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.