MDM 2020 Workshops

Apart the PhD Forum, three workshops will be co-located with this edition. The list with a short description fellows. More details are provided in the workshop website.

2nd Maritime Big Data Workshop (MBDW)

The growth of the maritime sector has produced an increase of the global maritime traffic and of the activities exploiting the ocean environment and its resources. Safety and security of maritime navigation remain a concern, like the global societal objective of reducing the environmental impact of maritime activities to pursue a sustainable and inclusive “blue growth”. Technological innovations led to the development of automated monitoring systems and maritime sensors networks, producing a tremendous increase of the maritime data available and opening new avenues to interdisciplinary science-driven maritime operations and policy making. Institutional and industrial initiatives are developing infrastructures for maritime data sharing and offering advanced processing, fusion, and analysis, developing added values products in support of the maritime operational and industrial communities, policy making and informed citizenship.The Maritime Big Data Workshop 2020 is organised under the umbrella of the 21st IEEE International Conference on Mobile Data Management (MDM 2020). It will be an opportunity for researchers, technology providers, institutions participating in interdisciplinary big data initiatives, and representatives of the operational community, to meet and exchange on research results and innovations in maritime.The workshop will welcome the presentation of novel big data computational solutions with application for maritime security, safety and security of maritime navigation and transport, Maritime Intelligent Surveillance and Reconnaissance, Maritime situational awareness, maritime environment monitoring and preservation, estimation of the impact of maritime activities on the maritime environment, sustainable fisheries and exploitation of ocean resources, energy efficiency and performance analysis.


  • Cyril Ray, Arts et Metiers Institute of Technology, Ecole Navale, Naval Academy Research Institute (IRENav), Brest, France
  • Elena Camossi, NATO Science and Technology Organization, Centre for Maritime Research and Experimentation, La Spezia, Italy
  • Christophe Claramunt, Arts et Metiers Institute of Technology, Ecole Navale, Naval Academy Research Institute (IRENav), Brest, France

International Workshop on Mobile Data Management, Mining, and Computing on Social Networks (Mobisocial)

Social network and mining research has advanced rapidly with the prevalence of the online social websites and instant messaging social communications systems. In addition, thanks to the recent advances in deep learning, many novel applications with mobile devices and social networks have been proposed and deployed. These social network systems are usually characterized by complex network structures and abundant contextual information. Moreover, by incorporating the spatial dimension, mobile and location-based social networks are now immersed in people’s everyday life via numerous innovative websites. In addition, mobile social networks can be exploited to foster many interesting applications and analysis, such as recommendations of locations and travel planning of friends, location-based viral marketing, community discovery, group mobility and behavior modeling. Researchers are increasingly interested in addressing a wide spectrum of challenges in mobile social networks to extract useful knowledge and exploiting location-based and contextual information embedded with mobile social networks to find out useful insights. The insights can provide important implications on community discovery, anomaly detection, trend prediction with the applications in many domains, such as recommendation systems, information retrieval, future prediction, and so on. In light of the above crucial need, sophisticated data mining, machine learning, and query processing techniques on both social and spatial dimensions are demanding for extracting representative information from mobile social network. In addition, the data generated from social networks and social media streams at any time in any place have outpaced the capability to process, analyze, and mining those datasets. It is thus imperative to develop scalable and efficient algorithm for processing and mining Big Data generated from mobile social networks. In contrast to other areas in data management and mining, social and human factors are also important and thereby encouraged to be properly included in multidisciplinary and interdisciplinary research of mobile social networks. The 5th International Workshop on Mobile Data Management, Mining, and Computing on Social Networks (MobiSocial 2020) will serve as a forum for researchers and technologists to discuss the state-of-the-art, present their contributions, and set future directions in data management, machine learning and knowledge mining for mobile social networks.


  • Wang-Chien Lee, Pennsylvania State University
  • De-Nian Yang, Academia Sinica
  • Hong-Han Shuai, National Chiao Tung University
  • Chih-Ya Shen, National Tsing Hua University

(3SCity-E2C) Building Software Services in Smart City through Edge-to-Cloud orchestration Workshop

As cities change and overgrow, smart city services contribute potent tools for enhancing livability, sustainability, and overall efficiency. Internet of Things (IoT) technology is considered as the heart of a smart city environment to develop the lives of the citizens within it. The IoT-enabled smart city may help to reroute traffic around congestion in real-time, automatically schedule repairs for failed infrastructure like street lighting, and intelligently organize energy and pollution consumption right across the constructed environment. It can defend citizens and businesses from violations as well as safeguard vulnerable citizens in their homes.
By 2021, Gartner envisages that 25 billion IoT devices will be connected and in use as well as assuming prominent business possibilities. However, to benefit fully from capabilities of IoT and thriving innovations in application domains such as applications of the energy management system (EMS), human health applications, etc. in the smart city, it is critical to facilitate the creation and operation of large-scale IoT systems management in the smart city. IoT systems are known to be complex, large scale, and distributed. Coordinated behavior across IoT, edge, and cloud infrastructures require to be organized and structured. Furthermore, trustworthiness of such systems is critical, ranging from business-critical to safety-critical. The capacity to continuously grow and conform to these systems is crucial to assure and develop their trustworthiness, quality, and user experience.
Edge-to-Cloud orchestration can offer a splendid solution for building Software Services across the city as well as management of the large-scale IoT in smart cities. With regard to focus on designing large-scale software services, we should consider data as the most precious resource for service development in smart cities. Without data, services cannot be launched for smart city citizens. Therefore, to build efficient smart city services, we should consider large-scale IoT data management architecture from data collection to data consumption as well as assessment and mitigation cybersecurity threats/risks to validate security requirements for building software services in the smart city.
Building Software Services in Smart City through Edge-to-Cloud orchestration (3SC-E2C) workshop focuses on software-assisted environments for urban environments. We welcome strong papers exploring the theme of “Large-Scale Data Management to build Software Services in Smart Cities” mainly concentrating on Edge-to-Cloud orchestration. This workshop brings together researchers, developers, practitioners, and stakeholders interested in the advances and applications for smart cities. In addition to this, we look forward to novel proposals for the large-scale management of data, software/service, and cybersecurity in the smart city environment. "


  • Amir Sinaeepourfard, Norwegian University of Science and Technology (NTNU), Norway
  • Antonio J. Jara, University of Applied Sciences Western, Switzerland
  • Antonio Salis, Engineering Sardegna, Italy
  • Deepak Puthal, Newcastle University, UK
  • Phu Nguyen, SINTEF, Norway