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Multiple ASpects TrajEctoRy management and analysis

Periodic Reporting for period 2 - MASTER (Multiple ASpects TrajEctoRy management and analysis)

Reporting period: 2020-03-01 to 2023-12-31

The problem to be addressed is related to the ever-increasing number of location devices producing massive amounts of traces of moving objects. These traces are called trajectories and they can be enriched with semantic information representing the different contextual aspects of the movement. We deal with trajectories where semantic aspects are intimately correlated and should be considered as a whole.
The overarching objective of the MASTER is to form an international and inter-sectoral network of organisations working on a joint research programme in the field of holistic trajectories. We build, manage and analyse holistic trajectories by considering as vital issues the privacy and big data related aspects.
We propose methods and techniques to analyse and infer useful knowledge from these multiple-aspects traces.
This is important for our society since many applications can benefitting from the methods developed in MASTER. For tourism, we collaborate with the Municipality of Thira in Santorini analysing their data to a picture of tourists flows for sustainability.
Sea monitoring better understands the ships movemen in the Mediterranean Sea are to identification of Search and Rescue operations and fishing effort in the Adriadic sea
Public transportation sector by analysing data form the Venice transportation agency to better highlight the movements of residential and tourists population in the area.
MASTER consortium is assisted by an Independent Ethics Advisor that helped the researchers in better understand the possible ethical implications of trajectories analysis
The scientific workplan of MASTER is organized into three working packages.

In WP3 we propose methods for managing and building semantically rich trajectories from heterogeneous and multidimensional data.
One main achievement is that we have defined a conceptual model called "MASTER" for representing multiple aspects trajectories together with a database implementation using the a graph based approach for semantic information, called Resource Description Framework (RDF) model, and a semi-structured database called NoSQL database.
This contribution is overall cited in the community and gave rise to a new filed of research.
Another achievement is that we developed methods to enrich trajectories – specifically ships trajectories that can be enriched for example with metereological or water information - with user annotations by means of a visual interface named VISTA.

In WP4 we study data analysis methods capable of taking into account the different aspects of holistic trajectories. We focus specifically on: similarity analysis, clustering, graph analysis, prediction and recommendation.
Main achievements include a similarity method for multiple aspects trajectories called MUITAS, in collaboration between National Research Council of Italy and Federal University of Santa Catarina in Brazil. This measure is useful when we need to compare trajectories with several heterogeneous semantic aspects, for example in recommendation tasks or in clustering methods. This method is consistently cited in the literature as a reference method for this kind of trajectories.
We also developed a method for predicting the fishing effort in the Adriatic Sea in collaboration between University Ca’ Foscari of Venice and Dalhousie University. This result can be exploited by several stakeholders like local/regional Administrations, Ministry of Agricultural, Food and Forestry Policies, Fishermen associations.

In WP5, we study the impact of the holistic trajectories analysis methods into the tourism, sea monitoring and public transportation domains. Main achievements is the collection of the datasets provided by Thira to study the tourism impact in the island and we are studying how to exploit social media to predict the arrival flows in the island. We also have collected and studied the vessels trajectories provided by the Dalhousie University and the University Ca’ Foscari of Venice. These ships movements may impact the sea wildlife (e.g. fishing) that is a topic studied by the University of Venice researchers during their secondments to Dalhousie. Other interesting results are methods for the analysis of vessels trajectories in the Mediterranean Sea to identify Search and Rescue operations, activities developed by the Harokopio researchers in secondment to Dalhousie University.
All these activities consider the Privacy and Big Data principles.

All our results have been disseminated into events and publications reaching a considerable number of readers / attendees. We participated in more than 50 scientific events and more than 10 communications events reaching a total of about 20.000 persons.

Partners are now exploiting the results in several directions: stimulate new research challenges that brought to new project submissions and new research publications.
The project has provided relevant research outcomes in the fields of movement data analysis, social media analysis, efficient data storage solutions and privacy preserving methods for movement data.
The potential impact of the project is towards the many applications that exploit movement data in any field.
The more than 50 peer reviewed publications in prestigious venues testify the outstanding research advancement in the field.

As the project specifically focuses in three application scenario, we expect to have more impact in Tourism, Sea Monitoring, Public Transportation.
Regarding the tourism scenario, tourism has the potential to contribute towards employment and economic growth, as well as to development in rural, peripheral or less-developed areas. One of the project partners, the Municipality of Thira in the Samtorini Island has the potential to exploit the results of the project to create a Destination Marketing Organization in the island.
As second application scenario, the Sea Monitoring and Migration flows, we observe how Europe experienced the greatest mass movement of people since the Second World War. The EU is improving security at borders with a new border and coast guard, tackling people smuggling and offering safe ways for people to legally enter the EU. The MASTER staff is acquiring new skills on how to combine and analyse heterogeneous data sources to better understand the migration phenomenon. These methods, developed in MASTER, could support the better understanding of the migrants flows to detect Search And Rescue (SAR). MASTER can also support the fishing activities and results from MASTER can be exploited my ministries of Agriculture and fishermen associations. The Public Transportation application naturally fits the “Smart, green and integrated transport” H2020 Societal Challenge specifically aiming at “a better mobility, less congestion, more safety and securitywith a substantial reduction of traffic congestion”. The methods study the use of public transportation to better understand their usage so that the transport companies can make actions to favor the use of public transportation. We believe that MASTER analysis methods can make a contribution to improving the public transportation usage as from the desiderata of the municipalities directly or indirectly involved in the project.
Leaflet of MASTER (verso)
MASTER poster
Leaflet of MASTER (recto)