The Piraeus AIS Dataset for Large-scale Maritime Data Analytics

The Piraeus AIS Dataset for Large-scale Maritime Data Analytics

Highlights
AIS data collected by the University of Piraeus' AIS receiver Contributors: Andreas Tritsarolis; Yannis Kontoulis; Yannis Theodoridis Data Science Laboratory, University of Piraeus Abstract The advent of Big Data and streaming technologies has resulted in a swarm of voluminous, heterogeneous information, especially in the domains of Internet of Things (IoT) and transportation. Focusing on the maritime field, we present a dataset that contains vessel position information transmitted by vessels of different types and collected via the Automatic Identification System (AIS). The AIS dataset comes along with spatially and temporally correlated data about the vessels and the area of interest, including weather information. It covers a time span of over 2.5 years, from May 9th, 2017 to December 26th, 2019 and provides anonymised vessel positions within the wider area of the port of Piraeus…
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ST-Visions

ST-Visions

Highlights
A Python-based library for interactive spatio-temporal data visualization. Overview ST_Visions (Spatio-Temporal Visualizations) is a python library, able to interactively visualize spatio-temporal data in a quick-and-easy way. Based upon the functionality of Bokeh, and further extending it, we are able to create powerful and cohesive visualizations (and/or online dashboards), for large or streaming spatio-temporal datasets. Paper: Link GitHub repository: Link Contributors: Andreas Tritsarolis, Christos Doulkeridis, Yannis Theodoridis and Nikos PelekisData Science Laboratory, University of Piraeus
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MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories

MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories

Highlights
Video Presentation: Contributors: Andreas Tritsarolis, Yannis Kontoulis, Nikos Pelekis and Yannis Theodoridis Data Science Laboratory, University of Piraeus Related Papers: MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories (SSTD’21 Best Demo Paper Award) GitHub repository: Link Contact: Andreas Tritsarolis <andrewt@unipi.gr>
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i4Sea: Surveillance and Analysis of Marine Areas Movement using Big Data

i4Sea: Surveillance and Analysis of Marine Areas Movement using Big Data

News
The final review of the i4Sea project was successfully held on November 11, 2021. During this 3-year project (July 2018 - July 2021), an innovative platform for the collection and analysis of large marine surveillance data was developed. The vision of the project was to efficiently and quickly process, integrate and analyze these data in order to create (a) a “Combined Real-time Business Image” and (b) a “Combined Historic Image” of Marine Surveillance. More details about i4Sea are available in the project’s official web site.
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Data Science Lecture Series, Fall semester, 2021-22

Data Science Lecture Series, Fall semester, 2021-22

News, Upcoming Events
The fall 2021-22 edition of the Data Science lecture series, provided by the Data Science Lab, consists of the following lectures:@ Wed. 8/12/2021, 19:45-20:45: Prof. Athena Vakali (AUTH) - Bot Detection in Online Social Networks@ Mon. 10/1/2022 18:30-19:30: Dr. Nikos Giatrakos (TU Crete) - EasyFlinkCEP: Big Event Data Analytics for Everyone@ Wed. 12/1/2022, 18:30-19:30: Prof. Periklis Andritsos (Univ, Toronto) - An Inside Look at Customer Journey Analytics@ Mon. 21/2/2022, 18:30-19:30: Dr. Foteini Valeonti (UCL & USEUM.org) - Blockchain, NFTs and Culture Free participation via MS Teams (link)
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BLUE RESEARCH AND INNOVATION DAYS – the Data Science Lab is there!

BLUE RESEARCH AND INNOVATION DAYS – the Data Science Lab is there!

News
The main objective of Blue Research and Innovation Days is to present ongoing cutting-edge projects along with a specially-shaped hackathon towards bringing together consortia, the scientific community and industry working at the core of the ‘blue economy’ by promoting synergies as well as shaping common future activities. The event will give the opportunity in every project to present its particular objectives, the current results, its cloud services, Open and Big Data research and results, the possible business cases providing by this way the possibility to the participants to investigate common approaches to specific problems, complementarities, synergies perspectives, future collaborations. The hackathon at the end of the week will integrate challenges from three specific projects towards providing the participants access to real world scenarios, business cases and open issues. Thus, it…
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