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DATASET2050 Report Summary

Project ID: 640353
Funded under: H2020-EU.3.4.

Periodic Reporting for period 1 - DATASET2050 (Data driven approach for a Seamless Efficient European Travelling in 2050)

Reporting period: 2014-12-01 to 2016-05-31

Summary of the context and overall objectives of the project

"DATASET2050 (DATA driven approach for a Seamless Efficient Travelling in 2050) is a Coordination and Support Action (CSA) funded by European Commission under H2020-Call MG.1.7-2014: Support to European Aviation Research and Innovation Policy; Grant Agreement no: 640353. The CSA - sometimes simply referred as "project" - is coordinated by Innaxis, with EUROCONTROL, University of Westminster and Bauhaus Luftfahrt as partners. DATASET2050 was launched during December 2014 and will last 36 Months, ending December 2017.

The project addresses the EU passenger mobility in the context of the door-to-door (D2D) objectives defined in the Flightpath 2050 vision. Specifically, the following is the list of overall objectives, challenges and how these are being faced in the project:

-To provide useful insight into the door-to-door European travel paradigm through a cutting edge data science approach for the present, 2035 and 2050 transport scenarios.
-Taking a passenger-centric approach, paving the way for a seamless and efficient door-to-door travelling experience.
Through this approach, the focus is to analyse how the European transport supply profile (capacity, connections, business models, regulations, intermodality, processes, infrastructure) could adapt to the evolution of the demand profile (customers, demographics, passenger expectations, requirements).
-To identify European transport bottlenecks and improvement areas across the different scenarios, through expert application of state-of-art predictive analytics, modelling, statistical analyses, data visualisation, along with an examination of multimodal data.
-These findings will serve as a basis for the development of intermodal transport concepts by identifying possible solutions for current and predicted shortcomings. The insights gained through the project's approach will also highlight research needs for the four hour door-to-door goal formulated by ACARE.

DATASET2050 partners are supported by an Advisory Board, which is comprised of top European transport entities (universities, policy makers, airlines, industry, research institutes, GIS and inter/multi-modal entities) who provide major inputs into European strategy agendas. In parallel a number of workshops will be useful for the project in terms of receiving external feedback from mobility stakeholders. The comprehensive dissemination and communication plans aim to ensure efficient circulation of the results among key European transport policy makers and stakeholders."

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In DATASET2050, work-packages 2, 3, 4 and 5 are those covering scientific and technical tasks, totalling nine scientific deliverables. In summary, WP2 tackles the data driven architecture (relevant datasets identification plus designing, building and tuning the data-driven model); WP3 covers the demand profile (current 2014 and future ones 2035 and 2050) whilst WP4 analyses the supply profile (current and future ones 2035 and 2050). Finally WP5 will provide an assessment of novel concepts and derive conclusions and recommendations.

The tasks performed from the beginning of the project to current reporting (first 18 months) have been: those linked with WP2, now fully finished, on the data driven architecture, and the first halves of WP3 and WP4 (so covering current demand and supply profiles). Additionally, WP5 has been kicked-off and received some results from WP2 tasks. Namely, the work performed has been:

-Looking at the requirements of the data to feed the DATASET2050 model at all its phases (i.e. door-to-kerb, kerb-to-gate, gate-to-gate, gate-to-kerb and kerb-to-door).
-Conducting an intensive review on what data are available, together with analysing temporal/geographical coverage, granularity, cost etc. Data acquisition tasks. Deliverable 2.1 was completed by January 2016.
-Designing and developing a visual tool that enables an easy exploration of the datasets, available at:
-Developing a data driven model capable of simulating the door-to-door processes. Deliverable 2.2 describing the key details of the model was recently finished and uploaded in ECAS June 2016.
-Completing the current demand profile, including the current mobility details (passenger behaviour, demographics, passenger expectations, requirements), is reported in D3.1 and has provided key input for the corresponding model part (demand). Deliverable 3.1 has been uploaded in ECAS in July 2016.
-The current supply profile includes research on what is the current level of capacity, connections, business models, regulations, intermodality, processes, infrastructure. This is reported in D4.1, which is currently work in progress and will be submitted to ECAS in the following months (October 2016).
-Providing inputs from all the finished tasks and deliverables to WP5. Specifically, D5.1 reports on the mobility assessment at all levels/scenarios, hence require inputs from all project stages.

In addition to the technical deliverables, DATASET2050 has punctually prepared and sent all the management and dissemination deliverables and reports. These covered the management and dissemination guidelines in addition to the reporting of the activities achieved so far. Specifically, those planned for this first period have been:

-Management plan (D1.1), Dissemination Plan and Material (D6.1), delivered on M1 (January 2015).
-First period management report (D1.2), delivered on M18 (June 2016).

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

"DATASET2050 aims to have socio-economic impact in the context of how EU door-to-door "transport" performs, and predicting how it will perform in the future. In the long term, DATASET2050's outcome will contribute to fewer disruptions and smoother travel for passengers.

The first progress beyond the state-of-the-art is calculating what are the current D2D mobility metrics. This way, a better holistic passenger-centric view will be accomplished, putting the first milestone in the path of providing D2D quantitative metrics further than the already available qualitative analyses.

In parallel, by using the data-driven model developed in the project, DATASET2050 will try to predict what will be the bottlenecks in future mobility scenarios (2035 and 2050). This prediction will include assessing and analysing how compressible the D2D sub-segments are; what are the potential futuristic scenarios; which will tentatively be the future demand and supply profiles in transport etc.

As this is the mid-term report, further and more detailed impact achieved by the project is expected for the second (and final) report, once the model is deployed and the assessment is complete."

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