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Dagstuhl Seminar 22022

Mobility Data Analysis: From Technical to Ethical

( Jan 09 – Jan 12, 2022 )

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Please use the following short url to reference this page: https://www.dagstuhl.de/22022

Organizers

Contact


Schedule

Motivation

Mobility data is one of the fastest growing types of data, thanks to the increasing number of mobile devices approaching the population of the globe. The collection, storage and analysis of spatio-temporal data representing trajectories of moving objects is one of the topics that received major attractions in the field of data analytics. The more semantic information is collected from various sources, the richer is movement data. This enriched mobility data is typically referred to as semantic trajectories. The analysis of such trajectories can produce powerful results in domains such as transportation, security, tourism, health, environment and even policy design. The recent COVID-19 outbreak shed a light on the importance of collecting mobility data for public health. However, at the same time, the more mobility data is enriched with semantics, the larger the risks of violating the privacy of users and of possible unethical uses of these data analysis results. Computational Ethical aspects encompass privacy, but they go beyond this, towards a more general vision of ethical gathering, processing, uses of data and the results of data analyses. How ethics interrelates with mobility data analysis is an emerging new issue.

The objective of this Dagstuhl Seminar is therefore to start a deep interacting discussion between Mobility Data Analysis researchers and Ethics experts to link these two fields with the objective of creating the foundations of a new Mobility Data Ethics research field.

The organizing team — Stan Matwin, Bettina Berendt and Chiara Renso — would be delighted to welcome you to this very special event.

This seminar, in the tradition of the Dagstuhl Seminars, promotes personal interactions and open discussions with the objective of producing joint tutorials and a vision paper. The seminar is organized in three full days that combine a "Setting the stage" session with introductory tutorials on both mobility data and ethics and a "Creating Mobility Data Ethics" session organized into small working groups discussing results, ideas, and open problems. As a first concrete step, we envisage that the Seminar will produce tutorial materials presenting each of the areas of Computing Ethics and Mobility Data Analytics, revised during the seminar based on the joint work and group discussions. Furthermore, group discussions will produce one or more short technical/vision papers that can foster discussions and initiatives to shape the new field of Mobility Data Ethics.

This seminar is nicely co-located with the Dagstuhl Seminar "Mobility Data Science" to be held from Sunday, January 9 to Friday, January 14, 2022 and organized by Mohamed Mokbel (University of Minnesota, USA), Mahmoud Sakr (Free University of Brussels, BE), Li Xiong (Emory University – Atlanta, US), Andreas Züfle (George Mason Univ. – Fairfax, US). We plan to hold shared sessions and moments of interaction. Participants will have the chance to simultaneously participate in both seminars.

Copyright Bettina Berendt, Stan Matwin, and Chiara Renso

Summary

Mobility data is one of the fastest growing types of data, thanks to the increasing number of mobile devices approaching the population of the globe. The collection, storage and analysis of spatio-temporal data representing trajectories of moving objects is one of the topics that received major attention in the field of data analytics. The more semantic information is collected from various sources, the richer is movement data. This enriched mobility data is typically referred to as semantic trajectories. The analysis of such trajectories can produce powerful results in domains such as transportation, security, tourism, health, environment and even policy design. The recent COVID-19 outbreak shed a light on the importance of collecting mobility data for public health. However, at the same time, the more mobility data is enriched with semantics, the larger the risks of violating the privacy of users and of possible unethical uses of these data analysis results. Aspects of Computational Ethics include privacy, but they go beyond this, towards a more general vision of ethical gathering, processing, uses of data and the results of data analyses. How ethics interrelates with mobility data analysis is an emerging issue.

The objective of this Dagstuhl Seminar was therefore to start a deep interacting discussion between Mobility Data Analysis researchers and Ethics experts to link these two fields with the objective of creating the foundations of a new Mobility Data Ethics research field.

This Dagstuhl Seminar, organised by Chiara Renso, Bettina Berendt and Stan Matwin as an activity from and beyond the MASTER project [1] aimed at bringing together researchers from different disciplines from Computer Science, Mobility Analysis and Ethics to trace the path from a technical vision of mobility Analysis to an also ethics-based approach to the field.

The three-day seminar was structured into three main modules: (1) round-table presentations in which each participant presented him/her self with a question about Mobility and Ethics that represents his/her interest and an object to visualise this interest or serve as a starting point for further discussion; (2) three tutorial on "technical", "ethical" and "legal" aspects of mobility data; (3) the working groups to discuss the main topics of interest that emerged during phases (1) and (2).

As a result of the group discussions on participants' interests and the issues raised in the tutorials, we formed five main working groups:

  • What is/are the trade-off(s) between data privacy and data utility?
  • Mobility Data Anonymity (Can location data be really anonymous?)
  • Ethics of Mobility Data: What is unique? Which guidelines?
  • Mobility Data Analysis Ethics beyond the data
  • Mobility Data Analysis Ethics beyond humans only: Tracking animals and moral agency

The tutorials and each of the working groups are described in a chapter of this report. Like other Dagstuhl Seminar reports, these chapters aim at makign the scientific results re-usable and extendable by others. In addition, we also want to help others profit from our experiences with the videoconferencing and other media technologies that we employed and the interaction-design choices that we made. This last chapter is a reflection also on ethical aspects of the precluded and the newly added forms of mobility of scientists (and others) in meetings during and after COVID-19.

References

  1. Chiara Renso, Vania Bogorny, Konstantinos Tserpes, Stan Matwin, and José Antonio Fernandes de Macedo. Multiple Aspect Analysis of semantic trajectories (MASTER). Int. J. Geogr. Inf. Sci., 35(4):763–766, 2021.
Copyright Bettina Berendt, Stan Matwin, Chiara Renso, Fran Meissner, Francesca Pratesi, Alessandra Raffaetà, and Geoffrey Rockwell

Participants
Remote:
  • Darren Abramson (Dalhousie University, CA)
  • Christine Ahrend (TU Berlin, DE)
  • Bettina Berendt (TU Berlin, DE) [dblp]
  • Florence Chee (Loyola University Chicago, US)
  • Thiery Chevallier (Akka Technologies, FR)
  • Maria Luisa Damiani (University of Milan, IT)
  • Josep Domingo-Ferrer (Universitat Rovira i Virgili - Tarragona, ES) [dblp]
  • José Antônio Fernandes de Macedo (Universidade Federal do Ceara - Brazil, BR)
  • Sébastien Gambs (University of Montreal, CA) [dblp]
  • Ioannis Kontopoulos (Harokopio University - Athens, GR)
  • Peter Kraus (European Data Protection Board - Brussels, BE)
  • Fen Lin (City University - Hong Kong, HK)
  • Jeanna Matthews (Clarkson University - Potsdam, US)
  • Stan Matwin (Dalhousie University - Halifax, CA)
  • Fran Meissner (University of Twente, NL)
  • Anna Monreale (University of Pisa, IT)
  • Francesca Pratesi (ISTI-CNR - Pisa, IT)
  • Alessandra Raffaetà (University of Venice, IT)
  • Chiara Renso (ISTI-CNR - Pisa, IT) [dblp]
  • Paula Reyero-Lobo (The Open University - Milton Keynes, GB)
  • Geoffrey Rockwell (University of Alberta - Edmonton, CA) [dblp]
  • Yannis Theodoridis (University of Piraeus, GR)
  • Konstantinos Tserpes (Harokopio University - Athens, GR)
  • Karine Zeitouni (University of Versailles, FR)

Classification
  • Artificial Intelligence
  • Databases
  • Machine Learning

Keywords
  • mobility data analysis
  • privacy
  • ethics
  • artificial intelligence
  • machine learning