Why BMDA

Nowadays, we have the means to collect, store and process mobility data of an unprecedented quantity, quality and timeliness. This is mainly due to the wide spread of GPS-equipped devices, including new generation smartphones. As ubiquitous computing pervades our society, mobility represents a very useful source of information. Movement traces left behind, especially when combined with societal data, can aid transportation engineers, urban planners, and eco-scientists towards decision making in a wide spectrum of applications, such as traffic engineering and risk management. However, when these mobility data come in huge amounts, heterogeneous formats and possibly with privacy issues, novel methods have to be studied for proper analysis tasks. 

The International Workshop on Big Mobility Data Management (BMDA) is a series of workshops held since 2018 in conjunction with the Extending Data Base Technologies conference. The objective is to bring together researchers and practitioners interested in solutions for scalable data-intensive applications that manage and analyze big mobility data. BMDA themes include: 

• Fundamentals of mobility data analytics 
• Big data platforms for mobility data analytics 
• Parallel / streaming data processing for mobility analytics 
• Predictive analytics using mobility data 
• Complex event detection for moving objects 
• Visual analytics on big mobility data 
• Mobility-as-a-Service 
• Interactive traffic analysis with GPS data 
• Urban / maritime / aviation traffic flow forecasting 
• Urban / maritime / aviation travel time prediction 
• Integration / interlinking of mobility with societal data 
• Geosocial networks 
• Philosophical / ethical / privacy issues on mobility data analytics 

BMDA editions:

* BMDA 2024 with EDBT 2024 – March 2024 - Paestum, Italy 

* BMDA 2023 with EDBT 2023, March 23, 2023, Ioannina, Greece 

* BMDA 2022 with EDBT 2022, March 29, 2022, Edinburgh, UK 

* BMDA 2021 with EDBT 2021, March 23, 2021, Nicosia, Cyprus (virtual) 

* BMDA 2020 with EDBT 2020, March 30, 2020, Copenhagen, Denmark (virtual) 

* BMDA 2019 with EDBT 2019, March 26, 2019, Lisbon, Portugal 

* BMDA 2018 with EDBT 2018, March 26, 2018, Vienna, Austria 

BMDA proceedings are published at CSUR and are therefore open access. So far (2021 included), we count *28* published research papers and demos. 

Best papers are invited for submission to a Geoinformatica BMDA special issue. So far, *7* papers, long versions of workshop papers, have been published at Geoinformatica: 

BMDA'2020 SI (link):

• Tritsarolis, A., Chondrodima, E., Tampakis, P., Pikrakis, A., Theodoridis, Y. Predicting Co-movement patterns in mobility data. Geoinformatica (2022). DOI  
• de Oliveira e Silva, R.A., Cui, G., Rahimi, S.M. et al. Personalized route recommendation through historical travel behavior analysis. Geoinformatica (2021). DOI  
• Carlini, E., de Lira, V., Soares, A. et al. Understanding evolution of maritime networks from automatic identification system data. Geoinformatica (2021). DOI  
• Bonavita, A., Guidotti, R. & Nanni, M. Individual and collective stop-based adaptive trajectory segmentation. Geoinformatica (2021). DOI  

BMDA'2019 SI:

• Etemad, M., Soares, A., Etemad, E. et al. SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels. Geoinformatica (2020). DOI  
• Kontarinis, A., Zeitouni, K., Marinica, C. et al. Towards a semantic indoor trajectory model: application to museum visits. Geoinformatica (2021). DOI  
• Koutroumanis, N., Santipantakis, G.M., Glenis, A. et al. Scalable enrichment of mobility data with weather information. Geoinformatica (2020). DOI  
• Makris, A., Tserpes, K., Spiliopoulos, G. et al. MongoDB Vs PostgreSQL: A comparative study on performance aspects. Geoinformatica (2020). DOI  
• Varlamis, I., Kontopoulos, I., Tserpes, K. et al. Building navigation networks from multi-vessel trajectory data. Geoinformatica 25, 69–97 (2021). DOI  

BMDA'2018 SI:

• Nikitopoulos, P., Vlachou, A., Doulkeridis, C. et al. Parallel and scalable processing of spatio-temporal RDF queries using Spark. Geoinformatica (2019). DOI  
• Chatzikokolakis, K., Zissis, D., Spiliopoulos, G. et al. A comparison of supervised learning schemes for the detection of search and rescue (SAR) vessel patterns. Geoinformatica(2019). DOI  

Steering Committee

* Nikos Pelekis, Data Science Lab., University of Piraeus, Greece (email) 

* Chiara Renso, ISTI-CNR, Pisa, Italy (email) 

* Yannis Theodoridis, Data Science Lab., University of Piraeus, Greece (email) 

Acknowledgments

The BMDA workshop series has been partially supported by a number EU Horizon 2020 projects and grants, including: 

VesselAI
(Enabling Maritime Digitalization by Extreme-scale Analytics, AI and Digital Twins), 2021-23

MASTER
(Multiple ASpects TrajEctoRy management and analysis), 2018-22

Track&Know
(Big Data for Mobility Tracking Knowledge Extraction in Urban Areas), 2018-20

BigDataOcean
(Exploiting Ocean's of Data for Maritime Applications), 2018-20

MaaS4EU
(End-to-End Approach for Mobility-as-a-Service tools, business models, enabling framework and evidence for European seamless mobility), 2017-20

TT
(Transforming Transport), 2017-19

datAcron
(Big Data Analytics for Time Critical Mobility Forecasting), 2016-18

Recent Past Events

BMDA 2020 remote

BMDA 2019

BMDA 2018