DATASET2050 presentation at Data Science in Aviation Workshop (EASA, Cologne-Germany)

The annual event exploring Data Science in Aviation (ComplexWorld funded; organized by Innaxis) has recently celebrated its fourth edition this past September 8th 2016. The event was hosted on the EASA premises in Cologne, Germany . This year it highlighted a presentation of the DATASET2050 project, “Data Science for Mobility”, by project coordinator Samuel Cristobal (Innaxis).

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On the Data Science In Aviation event:

Previous editions of the Data Science in Aviation event were hosted in Madrid 2013, Paris 2014 and Brussels 2015. The popular event usually draws attendance from more than 80 individuals from top European and worldwide aviation entities (including Airbus, Eurocontrol, Boeing, EASA, Airlines, Airports, ANSPs, SESAR , Universities, etc) along with ICT and data-related entities (including CERN researchers, Fraunhofer, Infrastructure-related, and various universities). Notable presenters from the 2016 edition included EASA, Innaxis, NATS, Eurocontrol, Boeing, ENAC and Fraunhofer.

In terms of the event agenda and content, the presentations has traditionally outlined how data science is understood as a useful set of fundamental principles that support and guide the principled extraction of information and knowledge from aviation data. Furthermore, the discipline leans on well-known data-mining techniques, and goes far beyond these techniques with successful data-science paradigms which provide specific applications in various air transport areas (safety, performance, mobility etc).

 

On DATASET2050 Samuel’s presentation:

The event also highlighted a key presentation from Innaxis project coordinator, Samuel Cristobal. Samuel presented five different points on data science in aviation.

  • First, he explained how some of the data science tools, techniques and concepts have been used in the mobility context, specifically using the DATASET2050 project as a case example.
  • Second, Samuel explained the different door to door phases under analysis (door-kerb; kerb-gate; gate-gate; kerb-door), which helps to delve deeper in the different data science components within aviation phases.
  • Third, Samuel outlined the different links between project objectives and overall Flightpath2050 goals.
  • The fourth point explored mobility data in Europe, and the value of the DATASET approach in this context.
  • The presentation concluded with a fifth and final point announcing the next communication actions. The full presentation can be accessed here: https://www.dropbox.com/s/91julyl8gsij2k9/DATASET_SC_v1.pdf?dl=0

 

In sum, the fourth edition of the Data Science in Aviation event was an excellent opportunity for dissemination of DATASET2050. This was in conjunction with a fruitful exchange of ideas with other aviation data scientists, some of whom working with similar tools in other sub-areas far from mobility. We hope to continue this momentum of knowledge exchange and look forward to a potential fifth edition of the popular event.

 

You can watch DATASET2050 Samuel’s presentation here, and the rest of the event videos at Innaxis’ Vimeo channel.

Passengers’ environmental awareness and travel behaviour

Passengers’ travel behaviour can be influenced by various factors, such as disposable income, travel purpose, age group or technological affinity (see also #blogpost7 Passengers expectations: door-to-door travel and beyond). One of these influential factors is the environmental awareness of passengers and in which way it impacts – or even alters – travel behaviour.

Air transportation emits greenhouse gases and hence has a potential harmful effect on our environment in the form of CO2 emissions, for example. Passengers contribute to this by their choice of means of transport, their choice of holiday destinations and kilometres travelled (Cohen and Higham, 2011; Brouwer et al., 2008).

Overall, air travel passengers seem to have a basic understanding of the environmental impact and many also have pro-environmental values. However, according to several studies it does not result into behaviour changes of passengers yet. It is hence not a factor influencing their holiday planning, the choice of a destination and the type of transportation (Hares et al., 2009; Böhler et al., 2006). Research also reveals that the willingness of passengers to pay for carbon offsetting schemes, one possibility to neutralize emissions generated by one’s own journey without compromising the means of transport or influencing the decision on holiday destinations, is low as well (Eijgelaar, 2009; Mair, 2011).

The three main barriers towards pro-environmental behaviour change are a lack of alternative transport systems, the high value of holidays with the freedom to travel to every destination one wants, and the lack of feeling personal responsibility for climate change (Hares et al., 2009; Böhler et al., 2006). However, within some recent studies, evidence emerged showing an increasingly pro-environmental awareness in passengers’ mind-set and a willingness to actually change air travel behaviour in the future (Cohen and Higham, 2011; Gössling et al., 2009).

To sum up, environmental awareness among passengers seems to be already present but does not lead to current behaviour changes. This, among other factors, will be explored within DATASET2050 and it will be modelled how such drivers influence the travel demand of air transport passengers in the future.

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References

  • Böhler, S., Grischkat, S., Haustein, S. and Hunecke, M., 2006. Encouraging environmentally sustainable holiday travel. Transportation Research Part A: Policy and Practice, 40(8), 652-670.
  • Brouwer, R., Brander, L. and Van Beukering, P., 2008, “A convenient truth”: air travel passengers‟ willingness to pay to offset their CO2 emissions, Climatic Change, 90(3), 299-313.
  • Cohen, S.A. and Higham, J.E., 2011, Eyes wide shut? UK consumer perceptions on aviation climate impacts and travel decisions to New Zealand, Current Issues in Tourism, 14(4), 323-335.
  • Eijgelaar, E., 2009, Voluntary carbon offsets a solution for reducing tourism emissions? Assessment of communication aspects and mitigation potential, Transport and Tourism: Challenges, Issues and Conflicts, 46-64.
  • Gössling, S., Haglund, L., Kallgren, H., Revahl, M. and Hultman, J., 2009, Swedish air travellers and voluntary carbon offsets: towards the co-creation of environmental value?, Current Issues in Tourism, 12(1), 1-19.
  • Hares, A., Dickinson, J. and Wilkes, K., 2009, Climate change and the air travel decisions of UK tourists. Journal of Transport Geography, 18(3), 466-473.
  • Mair, J., 2011, Exploring air travellers‟ voluntary carbon-offsetting behavior, Journal of Sustainable Tourism, 19(2), 215-230.

EU Door-to-Door Mobility Workshop: 12th July 2016

We’re pleased to host and coordinate the first workshop examining EU door-to-door mobility.
An outline of sessions can be found below (abstracts are here).

Date: 12th July 2016. 10:30 – 17:00 (approx)

Location: 309 Regent Street, London W1B 2HW University of Westminster, UK

10:00 refreshments on arrival

Welcome and introduction – University of Westminster (PDF)

  • Session 1. Challenges of a data-driven model

The DATASET2050 model

The current state of mobility in EuropeUniversity of Westminster (PDF)
Which journeys are in scope when measuring the 4-hour door-to-door target?
What data sources are available for the current and future models?
Meeting the passenger’s demand: current and futureBauhaus Luftfahrt (PDF)
Challenges ahead: how will we model 2035 and 2050?
Assessing current supply and demand profiles.
Developing a new model for European mobility Innaxis (PDF)
What new metrics (and segmentations) do we need, apart from simply measuring average journey times?
Analytical approach – what metrics are needed?
What is the current status of such journeys – latest progress with the model.

  • Session 2. Further exploring the journey process phase by phase – where are the efficiency gains?

Door-to-kerbKai Nagel, Technical University of Berlin (PDF)
Improved airport accessibility: intermodal mobility; efficiencies of different modes (e.g. better utilisation of road-based modes – fuller cars/taxis; prioritisation schemes); modal shift; integration and passenger confidence.
Kerb-to-gateGenovefa Kefalidou, Horizon 2020 PASSME project (PDF)
Reducing door-to-door airport travel time for passengers in Europe.
Providing passengers with real-time information on predicted demand for airport services.
Improving the airport experience for passengers.
Gate-to-gateSteve Williams, NATS (PDF)
The impact of new SESAR solutions aimed at improving gate-to-gate operations, including free-routing, business trajectories, functional airspace blocks and ATM performance targets.
The role of wider EU policies such as Regulation 261/2004.

  • Session 3. Looking ahead to 2035 and 2050

Futures near and farChristoph Schneider, Munich Airport (PDF)
Evolution of demand – market maturities, new technologies and travel patterns.
From where will the key performance improvements come? – panel discussion (PDF)
Major improvements and barriers. Is the 4-hour target achievable – at what price? What should be the role of regulation and policy?
Close and wrap-upUniversity of Westminster (PDF)

Registration: Attendance is free of charge, however the number of places are limited.
Dynamic conversations and exchanges of views are encouraged at the workshop.

You’re cordially invited: EU Door-to-Door Mobility Workshop hosted by DATASET2050

The 4-hour door-to-door challenge in Europe – are we heading in the right direction?

The DATASET2050 project is pleased announce a one-day workshop in central London on Tuesday 12 July 2016 focusing on the 4-hour door-to-door challenge. The event will be hosted by University of Westminister.

The workshop will focus on the challenges facing the Flightpath 2050 4-hour door-to-door target, with presentations from the project team (Innaxis, University of Westminster, EUROCONTROL and Bauhaus), along with guest speakers from Heathrow and Munich Airports, NATS and the PASSME project. Sessions will consider the current journey process and where efficiency gains may come from, data sources, new metrics, and a look ahead to 2035 and 2050.

Attendance is free of charge, however the number of places are limited!

Register today at: http://www.dataset2050.com/eumobilityworkshop. A preliminary draft of the agenda is also available.

DATASET2050 is a Coordination and Support Action funded by the European Commission under the Horizon 2020 Mobility for Growth topic “Support to European Aviation Research and Innovation Policy” (MG.1.7-2014).

For additional questions, please contact Hector at hu@innaxis.org.

Mobility datasets exploration tool

Within the project, we have recently listed the sources of EU door-to-door mobility datasets, reports and papers. That information is crucial for us to build the subsequent data-driven tasks (including the model). On top of that, they could be extremely useful to anyone doing research or simply interested in the mobility topic.

Having this in mind, the consortium has developed a visual, interactive tool that provides all the information in a simple, attractive way.  By using a dynamic D3.js , it includes information about data sources together to their temporal data coverage, authors, description and availability

How it works? Click here: http://visual.innaxis.org/mobilityDataSETs/. The datasets have been categorized in 9 families, all of them relevant within mobility context.

  • Demographic
  • Passenger demand
  • Passenger type
  • Passenger behaviour
  • Door-to-kerb
  • Kerb-to-gate
  • Gate-to-kerb
  • Airside capacity
  • Competing services

By clicking in each of them (the text, right side), all the data sources available within that family are displayed. Doing a mouseover on each of them (right side), detailed information is given in a tool tip about the data coverage, sources etc. In the cases too many sources are available, scrolling is the way to see them all 🙂 Clicking on the [x] at the top brings you back to the main page.

enjoy!

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http://visual.innaxis.org/mobilityDataSETs/

 

April’s post: Mobility performance, KPAs

There are many performance targets for the European (air) transport system. It is clear that performance-based frameworks are needed and utilised, especially when decision makers need to act on legislative packages or when operational managers need to make procedural changes or decisions regarding technology. This overarching model of operations proves that any costly decision must ultimately result in an increase in performance.

Different performance frameworks look into different aspects of the European mobility framework, with varying goals that are not necessarily compatible or aligned in the same direction. To illustrate, ‘Flightpath 2050’ envisions an air transport system that improves safety levels but also guarantees time-related performance for the future passengers of Europe; up to four hours maximum door-to-door travel time for 90% of travellers using air as a mode. This number is not arbitrary, as it corresponds to the type of experience high-level experts envision for European passengers. However, punctuality and efficiency metrics are mostly flight-centric. Passengers are rarely considered in performance schemes and therefore very little is known about the actual door-to-door time performance from the passenger perspective. Decisions such as ‘when’ or ‘where’ to act in achieving this goal have proven to be more challenging than initially expected.

The European Commission Single European Sky Unit is working on ‘Reference Period 3’, which delves deeper into the performance scheme for air navigation service and network functions from 2020. This performance framework is very detailed, but unfortunately does not yet include provisions for passenger punctuality. Due to the complexity of different, non-interchangeable metrics, the KPAs and the different performance goals do not necessarily match.

SESAR and CleanSky have detailed, technical performance goals. By looking into specific technology developments or procedures, it is clear that their technologies will surely improve the performance of many concrete operational elements (e.g. runway performance or environmental impact in terminal areas, to mention two of them) – however it is yet unclear how much those programmes will contribute to passenger mobility.

In addition, traditionally, passengers have been categorised as ‘business’ and ‘leisure’ travellers. However, these traditional distinctions have become less distinct over recent years and will continue to do so in the future. This is driven by various developments such as newly emerging markets and cultural backgrounds, an ageing society, and increasing digitalisation within private and business life. Resulting passenger needs and expectations during their journey can thus differ to a great extent. This is reflected in their willingness to pay for extra services and time savings during their stay at the airport, for example. Therefore, the initial passenger group classification is not sufficient any more to properly address and integrate passenger requirements across the different transport modes. (D3.1 on passenger profiling 2.0 to be delivered soon!)

See you in the next blog post!

Mobility and performance (DATASET2050 postpost)

PERFORMANCE FRAMEWORKS

Different performance frameworks look into different aspects of the European mobility framework, with varying goals that are not necessarily compatible or aligned in the same direction. To illustrate, ‘Flightpath 2050’ envisions an air transport system that improves safety levels but also guarantees time-related performance for the future passengers of Europe; up to four hours maximum door-to-door travel time for 90% of travellers using air as a mode. This number is not arbitrary, as it corresponds to the type of experience high-level experts envision for European passengers. However, punctuality and efficiency metrics are mostly flight-centric. Passengers are rarely considered in performance schemes and therefore very little is known about the actual door-to-door time performance from the passenger perspective. Decisions such as ‘when’ or ‘where’ to act in achieving this goal have proven to be more challenging than initially expected.

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The European Commission Single European Sky Unit is working on ‘Reference Period 3’, which delves deeper into the performance scheme for air navigation service and network functions from 2020. This performance framework is very detailed, but unfortunately does not yet include provisions for passenger punctuality. Due to the complexity of different, non-interchangeable metrics, the KPAs and the different performance goals do not necessarily match.

SESAR and CleanSky have detailed, technical performance goals. By looking into specific technology developments or procedures, it is clear that their technologies will surely improve the performance of many concrete operational elements (e.g. runway performance or environmental impact in terminal areas, to mention two of them) – however it is yet unclear how much those programmes will contribute to passenger mobility.

PASSENGER PROFILING

In addition, traditionally, passengers have been categorised as ‘business’ and ‘leisure’ travellers. However, these traditional distinctions have become less distinct over recent years and will continue to do so in the future. This is driven by various developments such as newly emerging markets and cultural backgrounds, an ageing society, and increasing digitalisation within private and business life. Resulting passenger needs and expectations during their journey can thus differ to a great extent. This is reflected in their willingness to pay for extra services and time savings during their stay at the airport, for example. Therefore, the initial passenger group classification is not sufficient any more to properly address and integrate passenger requirements across the different transport modes.

(DATASET2050 D3.1 on passenger profiling 2.0 to be delivered soon!)

See you in the next blog post!

The evolution of passenger profiles and implications for future mobility

Traditionally, passengers were categorized according to their travel purpose which resulted in the two groups business and leisure travellers (Dresner, 2006). However, these traditional distinctions started to blur over the past years and will continue to do so in the future. This is driven by various developments such as newly emerging markets and cultural backgrounds, an ageing society, or an increasing digitalization within private and business life. Resulting passenger needs and expectations along their journey can thus differ to a great extent. This is reflected in their willingness to pay for extra services and time savings during their stay at the airport, for example. Therefore, the initial passenger group classification is not sufficient anymore to properly address and integrate passenger requirements across the different transport modes.

Different studies investigate passenger behaviour and preferences in order to define new passenger groups. A characterization by varying expectations along their journey instead of travel purpose leads to new passenger profiles like “urban hoppers”, “culture seekers” or “screenagers” (SITA, 2015; Initiative Airport Media, 2011). Relevant characteristics include, inter alia, the age of the traveller, the level of personal mobility, environmental awareness, the degree of required individualisation, technological affinity, or the expected exclusiveness of services. The “Future Traveller Tribes” study (Amadeus, 2015), for example, defines the “social capital seekers” that pursue personalisation according to their individual preferences and interests. These particular passengers are very keen on sharing their travel experience in different social networks in order to receive positive validation by other users. Ubiquitous connectivity is therefore an important requirement along the entire travel chain. Destinations are selected in order to achieve recognition by presenting a unique experience and potentially creating incentives for other travellers to visit these spots.

Each passenger group in the different studies is mainly described in a qualitative way and uses multiple attributes to classify a particular traveller type. Within DATASET2050, various studies have been gathered in order to obtain a more quantitative-based picture of associated travel behaviour. This data is applied to establish current and future demand profiles which are in turn used to assess future mobility needs and potential bottlenecks.

 

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Figure 1: Passenger classification according to aspired travel experience and use of technology throughout the journey (Sources: own depiction based on SITA (2015); Skift (2015); OAG (2014); Amadeus (2015); Initiative Airport Media (2011))

References

Amadeus (2015), Future Traveller Tribes 2030 – Understanding Tomorrow’s Traveller, http://www.amadeus.com/web/amadeus/en_1A-corporate/Amadeus-Home/Travel-trends/Travel-community-trends/Future-Traveller-Tribes-2030/1319623906608-Page-AMAD_SolutionDetailPpal.

Dresner, M. (2006), Leisure versus business passengers: Similarities, differences and implications, in: Journal of Air Transport Management, Vol. 12, Iss. 1, January 2006, pp. 28-32.

Initiative Airport Media (2011), Airport Private Traveller Study – Reiseverhalten, EInstellungen und Werte der Privatreisenden am Airport, GfK Mobilitätsmonitor – GfK Roper Consumer Styles, http://www.flughafenwerbung.de/studien/airport-private-traveller-study.html.

OAG (2014), OAG Trends Report: What is shaping air travel in 2015?, OAG Aviation Worldwide Limited.

SITA (2015), Air Transport industry Insights: The Future is Personal, SITA – A 360 Degree Report.

Skift (2015), Megatrends defining travel in 2015, Yearbook / Issue: 01, Skift Travel IQ.

SIDs 2015

Given DATASET’s long-term scope and air-transport oriented approach, this blog post addresses the upcoming SESAR Innovation Days (SIDs). Research outcomes are only beneficial when it is disseminated to other people/entities/agencies/stakeholders. Given that, please consider this post as part of the promotional obligation of the event, not to mention the presentation includes research threads that will be crucial for DATASET model development.

The 5th edition of the SESAR Innovation Days will be hosted by Università di Bologna, Italy from 1st – 3rd December 2015. The SESAR Innovation Days (SIDs) are the main vehicle through which SESAR (Single European Sky ATM Research) disseminates the results of its long-term and innovative research programme and the event has become a milestone in the European research calendar. Presently SESAR-WPE supports 26 research projects, 3 research networks and 20 PhD studies, and to date has funded more than 75 organisations. With the transition to SESAR 2020 and its Exploratory Research programme under the H2020 calls, Europe will continue to benefit from similar frameworks, leveraging the success of the present research programme and attracting new researchers and scientific disciplines to ATM.

The SIDs is coordinated by EUROCONTROL, as it’s been every year, and Innaxis, University of Westminster, and all of the DATASET partners will be attending as active participants. Interested in learning more about their participation in the SIDs? Continue reading below!

  • EUROCONTROL annually coordinates the event. In particular, Colin Meckiff (EUROCONTROL) is General Chair of the event, and Dirk Schaefer (EUROCONTROL) the Programme Chair. Although they are not directly involved in DATASET2050, they can be reached through Innaxis if you are interested!
  • The Programme Committee includes Andrew Cook (University of Westminster) and David Perez (Innaxis). Both will be more than willing to speak with you at the event regarding DATASET or the SIDs in general. Don’t hesitate to contact them should you have questions!
  • One of the main research priorities within Innaxis and University of Westminster has been exploring trade-offs between different stakeholders. For this particular SIDs, University of Westminster, Innaxis and Belgocontrol will present the paper “Controller time and delay costs- a trade-off analysis.” The paper will be presented within the technical session of the SIDs.
  • The EC four hour door-to-door goal requires additional work and analysis in order to be fully understood. This includes building new modelling tools in which the metrics and data analysis will help to understand how to fully achieve this goal. Innaxis has particular strengthen within the mobility research area, and the Horizon 2020 Coordination and Support Action DataSET 2050 (both coordinated by Innaxis) and the SESAR-CASSIOPEIA agent-based modelling framework may be of interest to you if you are working on mobility research challenges. Please do not hesitate to contact our architect of mobility tools for ATM, Samuel Cristóbal (sc@innaxis.org) and Jorge Martin (jm@innaxis.org) who will both be in attendance at the conference.
  • The ComplexWorld network has advanced very much within the last five years. The network coordinator Paula López (Innaxis) will give a presentation on the first day of SIDs, which will provide an overview of the ComplexWorld evolution since it was launched with key emphasis on the 2015 outcomes. Furthermore, ComplexWorld will participate in the research Tournament on Wednesday Dec. 2nd. Please feel free to talk with Paula (plc@innaxis.org) if you are interested in additional information.
  • For a few years, Innaxis has been working on new air transport metrics and indicators. Along these lines, we have been crafting a tool to compute metrics against real traffic data with advanced visual tools to help understand these complex metrics. On the day before SIDs (Monday Nov 30th), we will be hosting a workshop on air transport resilience metrics: The 2015Resilience2050 Workshop. Registration is free and more information can be found here:http://resilience2050.innaxis.org/workshop-2015-bologne-sids/. Please contact Hector Ureta (hu@innaxis.org) for further information on the workshop and/or resilience research.
  • Data Science has also been an area of major interest for Innaxis in the last few years. We are working on different elements of a big data / data science infrastructure that allows major data mining for Air Transport across different fronts: from evaluating current delay propagation and the resilience of airports and airlines against disturbances, to evaluating new paradigms on safety monitoring; all of which is based on powerful deep analytics. We are very proud of our advancements in this area. Our colleague Massimiliano Zanin will be at the conference, and you can feel free to contact him (mz@innaxis.org) regarding this topic.
  • Complex network theory is also of same importance within Innaxis’s research and it has been increasingly used to study the air transport system by defining static or dynamic structures to characterise how airports are connected. Our ComplexWorld PhD student, Seddik Belkoura, will present a poster titled “A young person’s guide to the reconstruction of air transport networks” depicting how the sampling processes intervening in the construction of such structures can affect the topological stability of the final system’s representation. Please contact him if this is of your interest (sb@innaxis.org).
  • Also, Information Management has been an area of interest for us. In particular, we think the Data Science paradigms will only be fully enabled if data is shared across stakeholders. This can only be achieved if the right security and encrypted mechanisms are in place. Along these lines, there will also be a discussion about the main results of the SecureDataCloud project. Please talk to Massimiliano if you would like to learn more about Innaxis’s efforts in Information Management.
  • Last but not least, Innaxis will serve as a SIDs rapporteur and will help Eurocontrol to extract key conclusions and provide our own views on the future research avenues. Carlos Álvarez (Innaxis President) will facilitate this during the closing session. Please, contact Carlos (calvarez@innaxis.org) if you would like to continue the discussion!

Hope to see you in Bologna!

Hector Ureta

Passengers expectations: door-to-door travel and beyond

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Continuous use of smartphones, social media, checking rather than planning, instant access and sharing; these concepts are becoming more and more common. To pass people on the streets who are looking down to their screens is already the norm. Do they have an app to sense and avoid obstacles? Travelling and commuting time are becoming social media, news update, entertaining and, even, working time.

People are getting use to have access to information when needed, and the sharing of personal data, in a conscious, an unconscious way, is continuous. According to IATA, 98% of passengers want to have wi-fi at airports; internet access is becoming a basic product, such as water or electricity. All these data can be exploited by business, and particularly by airlines, to provide tailored products that target travellers’ preferences, even when those preferences have not even been made explicit. This proactive behaviour will allow airlines to become passengers’ travel companions on the door-to-door journey; and even beyond that by proactively suggesting trips and giving information prior and post travel time. Airlines that meet these expectations stand to gain a distinct competitive advantage.

The sense of control that passengers feel, by being able to choose and check information on their screens, allows airlines to increase revenues by targeting relevant products, while increasing passenger satisfaction, as their needs, real or generated, are meet instantly and proactively. Information can easily be adapted to the different phases of the trip. Timely and accurate information can significantly help on shortening door-to-door trips, particularly in case of disruptions.

Airlines are offering different services such as SMS, mails, specific apps, etc. Whichever the mean of communication used, the level of interaction with passengers is growing, and this creates on the passengers a new set of expectations that should be fulfilled. Passengers will be identified in different profiles to be able to deliver the most relevant information. These profiles might evolve as information is generated. Work needs to be done to provide common standards to ensure connectivity and that the relevant information is distributed timely. Big data, cognitive computing, intelligent search discovery systems and natural language processing are the core of these data analysis; data which is mainly generated in an unstructured way.

I am still not completely sure which is the most worrying e-mail I have received this week: the one from an airline kindly reminding me that I have not go anywhere on holiday this year and suggesting exotic destinations, or that other one with discounted flights to the city where my next meeting is scheduled

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