Domino goes door-to-door!

AUTHOR: Damir Valput

As an attentive reader of this blog might already know, Domino’s main goal is to collect evidence on how various implementations of mechanisms such as 4D trajectory adjustments (including Dynamic Cost Indexing, DCI), Prioritisation of Flights (such as  User Driven Prioritisation Process (UDPP)) and Flight Arrival Coordination using Extended Arrival Manager (E-AMAN), could impact the relationships between the elements of the ATM system. To obtain a fuller picture, Domino takes into account the passengers’ perspective in addition to the more traditional, flight-centred point of view.

While the focus of Domino lies primarily in the network effects that emerge from observing the gate-to-gate phase of air travel, the Domino team is also keen on understanding better the influence of the studied ATM mechanisms on the overall passenger experience. After all, in Domino we focus on the commercial air travel, and ignoring the passengers' experience in this era of increasing desire for seamless travel experience could be costly (read more about it for example here).

Seamless travelling experience has become an ubiquitous phrase nowadays and it usually understands a travel experience with the absence of disruptions on the whole itinerary from point A to point B, personalised to the travelling needs of each passenger (group). It is a concept of growing importance, especially when placed in the context of the goals of the Flightpath2050 document, produced by The Advisory Council for Aviation Research and Innovation in Europe (ACARE). In it, they formulated, among other objectives, a very ambitious goal of 90% of the passengers, travelling inside Europe, executing their door-to-door travel in under 4 hours. On the Image 2 you can observe how time distributions for the total door-to-door travel time differ for two very diverse passenger groups: younger people and families. On average, younger people complete their whole door-to-door journey in 5 hours and 10 minutes, which is 46 minutes shorter than what it takes people who travel with their families. The graph is borrowed from the project Dataset2050, for more information click here!

Network effects (about which you can read more in the previous post on the network centrality metrics) can tell us only so much about passengers' travel experience and how far away are we from the 4 hours door-to-door goal. Domino already incorporates passenger itineraries and will consider how elements in the system are linked among them and could have different degrees of relevance depending if flight-centred or passenger-centred metrics are considered. Flights can propagate reactionary delay through the network but passengers can miss connections too! However, In order to fully integrate the flight perspective and the passenger perspective, Domino will consider going door-to-door! In other words, Domino is going to implement a module that will model passengers' needs and time processes during the door-to-gate and gate-to-door part of the trip as well.

Moreover, other actors in the ATM system (airports, airlines, etc.) could potentially benefit from seeing themselves through the eyes of a passenger and capturing phenomena that emerge from the complex interactions through this shift in perspective. Including the model of the passengers' behaviour during their "out-of-plane experiences" could lead to observing new interesting effects in the air-travel network. How do mechanism studied in Domino influence passengers' door-to-door times? How do the mechanisms affect the criticality of elements in the network from a passenger perspective. Is there any relationship between the time passengers spend on various airport processes and type of the airport characterised by the newly developed centrality metrics? Those are just some of the questions this extension of Domino could help us answer.

Are you interested in what Domino has to tell us about the convoluted relationship between passengers and the rest of ATM actors? Then stay tuned!

PhD Candidate offer

Tadorea, in collaboration with the Universidad Politecnica de Madrid - Telecommunications Faculty, is currently seeking a PhD candidate to undertake his/her PhD programme in the Cryptography field as applied to aviation and, in particular, as applied to air traffic management (ATM).
Today's aviation operations utilize a set of large, heterogeneous, widely-distributed systems which are sometimes even composed of isolated sub-systems. These are highly complex and very difficult to model analytically, especially considering the interactions between them. Often, detailed data about these systems is needed to understand and benchmark their performance, set up targets, make policies or even plan shared network resources. In the last decade, access has improved to this type of data as well as the computing infrastructures required to store and perform complex calculations with such data. Some of those calculations are, for instance, machine learning algorithms which have also proven their usefulness. Aviation researchers are implementing solutions based on the latest deep learning techniques (, 2018).
That said, large datasets are not as available to aviation data researchers compared to data availability in other fields. Data science researchers face challenges related to the diversity of inhomogeneous data sources and the large volume of information to be handled and represented. However, the confidentiality of the datasets has historically been the most difficult barrier to data accessibility as most data owners have refused to provide access to significantly large datasets.
In this proposal, a potential approach is presented through the use of state-of-the-art cryptography techniques in overcoming this barrier. By painting some air traffic management data science problems as cryptography systems, and utilizing novel crypto-based solutions, the confidentiality barrier can be overcome without breaking confidentiality requirements. Private data could be used in ATM procedures and systems.
The selected candidate will join TADOREA´s research and development team in Madrid, Spain. His/her PhD thesis will be supervised by Pr. Dr. Victor A. Villagrá from the Telematics Department at the UPM-ETSIT who will be driving the research plan in applying state-of-the-art cryptography techniques to overcome data sharing barriers in the aviation sector. The combination of skills from the TADOREA and UPM-ETSIT teams will offer the candidate an ideal environment to develop his/her professional career in an environment with strong ATM-domain expertise and state-of-the-art data science, cybersecurity and privacy-preserving techniques.
The PhD programme is framed under the SESAR-Engage Knowledge Transfer Network and co-funded by it. As part of this network, the selected candidate will enjoy unique opportunities to participate in summer schools and conferences with other students and researchers in the field. The candidate will have access to a variety of datasets: from airlines, airports, air navigation service providers to other aviation stakeholders.
Talented and highly motivated individuals with a great dose of imagination, problem-solving skills, resourceful and data-driven passion are encouraged to apply.

Scientific goals:

  • Scientific goal 1 - Data privacy in aviation and ATM and challenges to improvements in procedures and system design
    The first scientific goal will be to advance the state-of-the-art in understanding how information sharing, using private datasets, can enable new ATM paradigms in performance assessment, policy and regulation and use of shared resources. Establishing the limitations of current solutions and proposing new systems and procedures shall lead to increased performance of the ATM along several KPAs. This in turn helps justify overhead in investment in research and development. Three different concrete scenarios will be defined corresponding to one different prominent challenge scenario in each line of work. Those scenarios should be representative of the line of work and simultaneously show significant barriers and impact potential.
  • Scientific goal 2 - Design of cryptographic systems for ATM
    The PhD candidate should then identify and design cryptographic systems that provide the functionalities sought after each ATM challenge scenario. The second scientific goal will be achieving a cryptosystem that guarantees accurate and secure computation, performs under a concrete communication infrastructure and improves the ATM performance.

Requirements are as follows:

  • A university degree in any of the related fields (Mathematics, Physics, Engineering), provided strong skills in Mathematics can be proven.
  • Basic understanding of cryptographic systems goals and design.
  • Strong background and experience in programming.
  • Experience with extraction, acquisition, preparation of data.
  • Fluency in English. Only candidates fluent in English should apply, as the interviews might be carried out in English.
  • Above all, a strong motivation in developing skills in privacy-preserving data analytics.

Other skills that may be relevant in the evaluation

  • Passion for data science on top of current thinking and trends
  • Proficiency in Python 3 and data science toolkits knowledge.
  • Familiar with distributed data processing architectures, e.g. Spark
  • Knowledge or experience with the air transport field.

Tadorea offers a unique set of benefits:

  • Immediate start - Candidates are mandated to start the PhD during Q1 2019. Only available candidates should apply.
  • Training, internal and external, on the work-related different technologies.
  • Integration in a highly qualified and collaborative international team with innovative thinking and agile working methodology.
  • Flexibility and good working conditions.

Gross salary: 22.000€
Interested candidates should send the following information to

  • An up-to-date and detailed CV in pdf format. References, academic records and proof might be requested afterwards but they are not necessary for initial application.
  • A research motivational letter, carefully explaining why she or he is the perfect candidate.
  • Sharing any professional Internet presence is highly recommended, such as GitHub and/or Stack Overflow profiles, website-blog, portfolio, LinkedIn account, etc.
  • Any other relevant information supporting the application.

Download the PDF version

When airlines and ANSPs come together


The project team came together for the last Consortium Meeting on November 6th and 7th in Majorca. Big thanks to Air Europa who supported and hosted the meeting.

For two days, five airlines (namely Air Europa, Iberia, Norwegian, Pegasus and Vueling) met with the 3 ANSPs participating in the project (Austrocontrol, ENAIRE and LFV), along with Eurocontrol, AESA and EASA (Spanish and European Safety Authority respectively). The last meeting was to collaboratively discuss their broad experience in safety. The group combination of airspace users, including pilots, ATCOs, FDM safety analysts, and safety authorities representatives provided a very inspiring and clear overview of present-day aviation safety analysis, its challenges and opportunities on the transition from event-driven to data-driven safety intelligence. These meetings provide critical insight for data scientists and are key to support the users-driven approach adopted for the project since its conception. The users have defined relevant safety scenarios where data science and ML techniques can provide an added value over the incident-analysis tools they currently have. The scenarios, Runway performance, unstable approaches, group proximity, and airprox drive the descriptive and predictive analytics for The consortium meetings are an important to present results from the data analysis and discuss and capture their requirements (both individually and in groups) for future work. As the final users of the data analysis work performed within, it is key to ensure this alignment so their visualization dashboards provides relevant and usable ML tools.

SafeClouds is currently immersed in running the analytics based on three years of FDM data, which is merged with traffic data from Eurocontrol, weather data and surface radar data, among other data sources as required by the use case. This comes after investing the first months of the project to develop the legal and technical framework for securely managing and protecting the data. Considering this, the DataBeacon development, a data infrastructure that through several security layers and applying innovative cryptographic techniques, enables the data protection and merging while preserving its confidentiality. This Aviation ML platform, and the different implemented features and applications, enables data analysts to perform their analysis over various aviation data sources without actually having access to the databases. In all, this provides the necessary level of trust to the users and data owners.

With these developments, is going one step further by providing breakthrough analytics on safety precursors based on ML techniques. This analysis will combine airline FDM data with traffic, ADS-B and METEO data, providing improved information on the scenario that individual airspace users cannot otherwise access. This provides airlines, ANSPs and airports an enhanced understanding on the main causes that influence a safety incident which can support decision making for developing customized mitigation actions. Interested in more details on the techniques and results? A follow-up post will be published soon.

Call for entry level or junior Data Scientists

Innaxis Research and Foundation ( is currently seeking for exceptional Data Scientists to join its research and development team based in Madrid, Spain. The position is directed towards talented and highly motivated individuals who want to pursue and lead a career in Data Science and Big Data outside of the more mainstream, conventional alternatives such as consulting or academia. Individuals with a great dose of imagination, problem solving skills, ambition and passion are encouraged to apply.

As a Data Scientist, you will mainly assist the team to understand, analyse and mine data, but also to prepare and assess the quality of such. You will also develop methods for data fusion and anonymization. Ultimately your goal will be to extract the best knowledge and insights from data, overcoming technical limitations and committing with regulatory requirements. You will also work closely with data engineers, you will help the engineers team to define the requisites for the Big Data architectures; covering the whole process of data gathering, processing and delivery. You will always need to be ahead and use the latest technologies and solutions for the ultimate performance and data insight.

About Innaxis

If not unique, Innaxis is at most not conventional: it is a private independent non-profit research institute focused on Data Science and its applications: most notoriously in aviation, air traffic management and mobility, among other areas.

As an independent entity, Innaxis determines its own research agenda and has now a decade of experience in European research programs with more than 30 successfully executed projects. New projects and initiatives are evaluated continuously and open to new opportunities and ideas proposed within the team.

Our team consist on a very interdisciplinary group of scientists, developers, engineers and program managers, together with an extensive network of external partners and collaborators, from private companies to universities, public entities and other research institutes.

Wish lists

Our team members work very closely, so broader knowledge means a much better coordination. The following list of skill defines the whole Data Scientist team at Innaxis. No not hesitate to apply, even if you don’t fulfil all the skills below. Hardly any single person does.

  • University degree, MSc or PhD on Data Science or Computer Science, or related field provided sufficient experience.
  • No professional experience required, although it might be positively evaluated.
  • Proficient in a variety of programming languages, for instance: Python, Scala, Java, R or  C++ and up to date on the newest software libraries and APIs, e.g. Tensorflow, Theano.
  • Experience with acquisition, preparation, storage and delivery of data,  including concepts ranging from ETL to Data Lakes.
  • Knowledge of the most commonly used software stacks such as LAMP, LAPP, LEAP, OpenStack, SMACK and similar.
  • Familiar with some of the IaaS, PaaS and SaaS platforms currently available such as Amazon Web Services, Microsoft Azure, Google Cloud and similar.
  • Understanding of the most popular knowledge discovery and data mining problems and algorithms; predictive analytics, classification, map reduce, deep learning, random forest, support vector machines and such.
  • Hands-on experience on most common visualisation tools: Tableau, Qlik, QuickSight, etc.
  • Continuous interest for the latest technologies and developments, e.g. blockchain, Terraform,
  • Excellent English communication skills. It is the working language at Innaxis.
  • Availability and wiling to travel to Europe and engage with our research partners and stockholders.
  • And of course, great doses of imagination, problem solving skills, ambition and passion.

Your benefits

The successful candidate will be offered a Innaxis’ position as a Data Scientist, including a unique set of benefits:

  • Being part of a young, dynamic, highly qualified, collaborative and heterogeneous international team.
  • Great flexibility and most excellent working conditions.
  • Long term and stable position. Innaxis is steadily growing since its foundation ten years ago.
  • A fair salary according to the nature of the institute and adjusted to skills, experience and education.
  • Independence, as a non-profit and research-focused nature of Innaxis, the institute is driven by different forces than in the private sector, free of commercial and profit interests.
  • The possibility to develop a unique career outside of mainstream: academia, private companies and consulting.
  • No outsourcing whatsoever, all tasks will be performed at Innaxis offices.
  • Opportunity to get around Europe while visiting our extensive partner network.
  • An agile working methodology; Innaxis recently implemented JIRA/Scrum and all the research is done on a collaborative wiki/Confluence.

How to apply

Interested candidates should send an email to containing:

  • An up-to-date and detailed CV in pdf, references, academic records and proofs might be requested afterwards but they are not necessary for applying
  • research motivational letter, explaining carefully why she or he is the perfect candidate.
  • It is highly recommended to include any professional Internet presence, such as GitHub and/or Stack Overflow profiles, website-blog, portfolio, LinkedIn account , etc.
  • Any other relevant information supporting the application

You will be contacted further and a personal selection process will start.

Aircraft, network, and zoology

It is well known that the problem of building a schedule plan for an airline is a difficult one. The core difficulty is indeed to take into accounts the multiple constraints of aircraft, crew, maintenance, passenger correspondence etc, while trying to capture as much market as possible, all with minimum expenses. It is similar to riding a bike... except you do not know who is riding, where the wheels are, where you are supposed to go and if you should buy a car instead.

One of the most important constraints is the aircraft, since:

  • it is impossible to fly without it (rockets are quite unsafe to land at airports),
  • it is quite expensive (I've been told).

Let's imagine that, as an airline, you roughly know what cities you want to connect and how many passengers should travel with you. Where should your existing aircraft fly? Should you buy one? Do you have different strategies if you are a low-cost carriers or a traditional one? This is roughly the answers that our agents are trying to answer in the second block of our Vista model, the "schedule mapper". Of course, since our model simulates all the airlines in Europe, we cannot dedicate as much time (real and computational) as airlines do in reality to their schedule plan. But, like for the other parts of Vista, we are trying to catch to main behaviours of the system.

As usual, we start from what we can observe from data. For instance, it is common to say that aircraft usually go back and forth, and that some of them do sometimes triangular flights. Is that true? To investigate this, we take a three days time window where we track the itineraries of aircraft in terms of airports, defined as "patterns", using DDR data. What kind of patterns 'live' in this environment? How to classify them?

First, like taxonomists do not care about the specifics of a single individual to make a classification, we should not take into account the details of the patterns to classify them (in fact, that's the definition of a classification...). So for instance Rome - Paris - Rome has the same pattern than Frankfurt - London - Frankfurt, which can be rewritten 1 - 2 - 1 for instance. If a specific sequence is an individual in zoology, a pattern is thus akin to a taxon.

We can roughly divide these taxons into two "reigns": the ones which are closed (more explicitly have at least one closed loop), and the rest. For instance, an aircraft doing Paris - Frankfurt - Rome - Paris - Rome - Paris in three days has a closed pattern, whereas an aircraft doing Rome - Madrid - Barcelona is open. Of course, in the long run, most of aircraft do at least one full loop, but in three days some of them cannot make it. However, when counted in number of flights, most of them are closed in 3 days already, as shown in the figure below. In the following, we focus only on these closed taxons. Pretty much like one could focus on a study on mammals for instance, except that in this case, the mammals represent most of the animal kingdom.

Among them, some are more elemental than others, in the sense that they cannot be constructed from their peers. These are the ones which have exactly one closed loops. The ones present in the data are represented in the figure below, with their frequency of appearance (the number n corresponds to the number of airports in the loop). Most of them are single returns (1 - 2 - 1), triangular flights (1 - 2 - 3 - 1), and rectangular flights (1 - 2 - 3 - 4 - 1), and we focus on these three ones in the following. Note that rectangular flights seem more frequent than triangular ones, perhaps contrary to the popular belief.

All the other patterns can be constructed from these elementary ones, and we name them 'combined' patterns. For instance, (1 - 2 - 1 - 2 - 1) is composed of two single back and forth. In terms of zoology, it is a bit like saying that an elephant can be obtained by gluing a snake to a hippopotamus. Or that a giraffe is really nothing more that a horse with a periscope in the throat, which personally I believe very much. In any case, it easy to plot the frequency of appearance of these combined taxons, as shown in the figure below. Since all of them are coming from three taxons, we use notation the (X, Y, Z), where e.g. (2, 0, 0) represents two returns, (1, 1, 1), a return, a triangular flight and a rectangular one, etc. Some very rare patterns have been omitted in the figure. As expected from the previous figure, most of the aircraft goes back and forth during the three days. It is interesting to see that triangular flights are very under-represented, and that it is more frequent to have a rectangular flights every now and then, in combination with returns. Note that when a pattern features several returns, it is not necessarily between the same airports (e.g. Warsaw - Oslo - Warsaw - Vienna - Warsaw). In fact, we found that most of the combined patterns are 'impure', i.e. they are composed of elementary patterns with different airports (like gluing two birds of different colours for instance).

What does Vista do with this freak zoo? Well, the way the airlines choose implicitly the different patterns is a complex procedure, driven by the different constraints cited above. So the idea is that the best patterns should be selected for their efficiency, much like some taxons are selected by evolution based on their fitness in the given environment. Each taxon has also some particularities. For instance, flights using the taxon (4, 0, 1) mainly departs (from their first airport) in the early morning,  whereas taxons (2, 0, 0) are used by flights departing more frequently in the late morning, and sometimes in the evening, as shown in the figure below. Other regularities can be found in terms of average turn-around times for instance.

In the model, we use all these data to build reasonable schedules by resampling the different taxons for each airline. This will be described in a later blog post. And no more weird animal crossings, we swear!

ANSPs, how changes on fuel price affect your airspace revenues?

AUTHOR: Luis Delgado

Vista allows to analyse complex scenarios with interactions between metrics of different stakeholders.

Flight plan generation and route selection

When airlines select their flight plans between a given origin and destination many different factors need to be considered, such as possible routes available, weather, aircraft performance or time required. Vista uses a data-driven approach analysing historical flight plans, routes between airports and aircraft performances to estimate the cost of operating those different routes.

As shown in the above diagram, the historical analysis of data allow us to generate a pool of two dimensional routes, probability distributions for cruise wind, speed and flight level request and length and duration of climb and descent phases. With this information, for each possible route we can estimate the 4D trajectories that the airline will plan and estimate the total operating cost of these possibilities.

A given flight will, of course, follow only one of the possibilities, so at pre-tactical level, the different flight plans options are prioritised considering their expected direct operating costs (as a function of flight time, fuel and en-route airspace charges). This selection is not deterministic as airlines not always will follow the apparent lest cost route and in Vista we are interested on reproducing realistic flight plan selections options, not the best option!


What if we change the cost of fuel?

Vista is a great tool to analyse the impact of changes of parameters such as fuel cost on the behaviour of the stakeholders in the system. In some areas of Europe, airlines face the possibility of selecting different routes which might incur on different airspace en-route charges and different fuel consumptions and flying time. This leads to trade-offs that can be captured by Vista. An example of one of those regions is western Europe and flights to-from the UK and the Canary Islands. As shown in this image, airlines can select more direct routes using the airspace of France, Spain and Portugal or operate longer routes which benefit from the low airspace usage cost of the Oceanic airspace.

The trade-offs between different metrics for the airlines can be explicitly computed by Vista as shown in the image below for different fuel price scenarios. With higher fuel cost, shorter routes tend to be selected leading to lower fuel usage but higher airspace en-route charges.

As Vista considers multiple stakeholders it is possible to assess the impact of these changes on the demand and expected revenue obtained by the different ANSPs as shown in the following images:

Expected revenue due to en-route charges variation for GCTS - EGKK flights

Expected revenue due to en-route charges variation for all of ECAC flights

The figure above shows the expected changes on revenues for the different ANSPs across Europe if changes of fuel price are produced. This illustrates how different parameters are interconnected for different stakeholders in subtle manners that can be captured by Vista: changes on fuel prices represent variations on routes preferences which might have an impact on airspace usage and revenues of the ANSPs!

The new report to the Club of Rome: Come On!

The human footprint is increasing fast and will —if not reversed— eventually lead to a collapse of the global economy. So say the authors of the new book Come On! which proposes an overhaul in the way that governments, businesses, financial systems, innovators and families interact with our planet.



About the book Come On!

About the Club of Rome

Now, in cooperation with more than 30 members from the Club of Rome, authors Ernst Ulrich von Weizsäcker and Anders Wijkman, co-presidents of the Club, suggest possible solutions to the global ecological and social crises. At the core is the suggestion to develop a new Enlightenment for a "Full World": we can no longer depend on a societal model that was developed for a world of less than one billion people.

Humans and farm animals constitute 97 percent of the bodyweight of all living land vertebrates on earth so it’s not surprising that the remaining 3 percent of wildlife struggles to compete for land and for survival. Alongside an environmental crisis are social, political and moral crises. Billions of people no longer put trust in their governments, poverty has deepened in many countries, in the US the middle-class is rapidly shrinking.

Measuring our success on GDP growth has proven inadequate to the task and it also masks a growth in inequality between rich and poor. New indicators such as a Genuine Progress Indicator could more accurately measure economic welfare.

The present model of development is seriously flawed. Profit maximization – under the principle of shareholder value first – and saving the planet are inherently in conflict. The new Enlightenment must be characterized by a vastly improved balance between humans and nature, between markets and the law, between private consumption and public goods, between short-term and long term thinking, between social justice and incentives for excellence.

Carlos Alvarez Pereira (President of Innaxis and member of the Club of Rome) contributed to the report with a chapter on the Digital Revolution, highlighting that advances in technology will be crucial in order to cope with environmental degradation. However technological disruption must be analyzed beyond the current hype that digitization is clean and exponentially opening up new possibilities. Instead the effects on resources depletion, climate change, and employment have to be carefully considered and addressed for a true sustainable and inclusive technological disruption.

This book comprises many practical examples, success stories and opportunities for the “Full World”. A move towards a circular economy can help overcome mineral scarcity, significantly lower carbon emissions and increase the number of jobs. Regenerative agriculture will help stop soil erosion, enhance yields and build carbon in the soil. Efforts have to be made to rein in the financial sector by increasing capital reserves and control of money creation. Some insights can come from the Hopi tradition in North America, which developed sustainable agriculture and maintained a stable population size while avoiding wars.

Civil society, the communities of investors, and the research and education communities should become strong players in the necessary transformation.


SafeClouds presentation at the IATA ADS

On November 15-16, 2017, IATA organised the first Aviation Data Symposium in Miami, FL USA. This event covered different angles of the application of engineering and data analytics to airline safety, operations, passenger distribution, sales, and air freight. These three areas were complemented by a technology track, which covered techniques and tools to support data activities in airlines. The safety and operation tracks discussed how big data is helping airlines to optimise operations while maintaining safety, and also presenting the upcoming main challenges.

The event also covered a review of the benefits from the various global information sharing and exchange networks, including the Global Aviation Data Management programmes coordinated by IATA. During the Symposium, Mr. Quevedo presented IATA data connect, the database of aviation accidents, IATA FDX, the GDDB and STEADES. ASIAS, the US data exchange programme was also presented by Mr. Madar, Managing Director of Operation Safety of American Airlines. Then, Mr. Hernández-Coronado, Director of Safety Analysis and QM of the Spanish Aviation and Security Agency (AESA) presented the European programme Data4Safety, that was recently launched by EASA in Europe.

Concerns regarding privacy remain very strong, as often, the privacy protocols are strict and de-identification could make data challenging to use, as explained by the programme representatives. Mr. Madar stressed new techniques and technologies that allow to progress on data privacy, together with new tools that allow to move from descriptive to predictive technologies, like machine learning, as an area that will help the programmes evolve, as the descriptive analysis done in the last decade, as done with ASIAS.

Mr. Hernández-Coronado presented SafeClouds in detail. AESA participates in the SafeClouds project and helps the team understand how different technologies researched in the project can help aviation data exchange programmes overcome some of the presented challenges. These challenges include data fusion and integration, data protection and privacy, and computing infrastructures. SafeClouds also investigates predictive analytic concepts and techniques to help aviation stakeholders make decisions, even during the operations.

Mr. Hérnandez-Coronado also covered the activities performed by the Spanish Aviation and Security Agency, particularly the Spanish SSP, State Safety Programme. This system receives and collects around 300-400 safety events per week. He also presented the RIMAS system, showing the capability of providing a complete risk assessment picture of the national safety status by combining a variety of data sources; ultimately providing analytical support for AESA so that they may focus their attention on those areas that require supervision.

Web Summit 2017


We are pleased to announce that Carlos Alvarez Pereira (President of Innaxis) will be participating as a speaker at the Web Summit taking place 6th-9th November 2017 in Lisbon.

The Web Summit is dedicated to connecting the technology community with a range of people from across the global technology industry, as well as with politicians, scientists and influencers. The Web Summit has grown to become the “largest technology conference in the world” with more than 6000 attendees participating this year.


Carlos will participate at the panel discussion ”Reducing carbon-intensive activity: Will we always have Paris?” on 8th November.

Other panelists will include Javier Garcia-Martinez (University of Alicante), Mohan Munasinghe (Planetiers), Femke Groothuis, (The Ex’tax Project) and Michael Kuhndt (Collaborating Centre on Sustainable Consumption and Production). The panel discussion will be moderated by Sam Geall (China Dialogue).

The panel will investigate the challenge of how to ensure the success of the Paris Climate Agreement, and how to effectively reduce carbon emissions when it conflicts with business interests. Incentives and strategies will be examined in order to re-align business interests with the urgent humanitarian need to address climate change and its disastrous consequences. For this, the role of behavioral change, technologies, political and economic incentives will be part of the discussion

Engaging with a new generation of change makers


Considering the intricate challenges humanity has to face such as climate change, social inequalities, migration, and technological disruption (just to name a few), we are in desperate need for a new generation of changemakers who are able to grasp the systemic and interconnected nature of the issues in order to design innovative approaches that overcome today’s barriers to change.

INX4PS is actively seeking to promote systems literacy and to engage with a new generation of changemakers to raise awareness as to how complex issues can be embraced.

In this context, INX4PS has participated at the first Club of Rome (CoR) Summer Academy, which took place 7th-13th 2017 September in Florence, Italy.


The Club of Rome is an eminent international think tank that launched in 2016 with the “Reclaim Economics” project, designed to transform the way our economic system is perceived and understood. It promotes new economic thinking that puts human well-being and the planet at the centre. The Reclaim Economics flagship event was the first Club of Rome Summer Academy in Florence.

The CoR Summer Academy has been attended by students and academics, young professionals, aspiring entrepreneurs, young journalists, artists and activists. The participants joined with some of the world’s leading social and systems thinkers to inspire economic, ecological, and political movements towards action.

Carlos Alvarez Pereira (President of Innaxis and member of the Club of Rome) gave insights on the issue of  “TECH FOR HUMANITY – REFLECTIONS ON THE TECHNOLOGY REVOLUTION”.

During the interactive dialogue with the Summer School participants, many items were discussed including the role of science and technology and its impact on social evolution, the consequences on sustainable development, and furthermore the meaning of “technological disruption”.

The core theme of the debate was the role of current mindsets which largely influences technological innovation outcomes, including how well society adapts and integrates these new technologies. Additionally, questions of technology’s overall purpose, and how to design technology while ensuring humanity is the beneficiary, spurred a dynamic discussion among the participants.

The event was attended by 120 participants from 25 different countries. Among the speakers included: Kate Pickett, Kate Raworth, Anders Wijkman, Ernst Ulrich von Weizsäcker, Mathis Wackernagel, Ugo Bardi, Jorgen Randers, Tim Jackson and many more who discussed challenges and proposals for addressing systemic challenges.

INX4PS is looking forward to further engaging with the new generation of changemakers, to introduce systems thinking, and to co-create the paradigm shift of the 21st century.

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