A Distributed Spatial Data Warehouse for AIS Data

Alex Skov Klitgaard, Lau Ernebjerg Josefsen, Mikael Vind Mikkelsen, Kristian Torp

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

AIS data from ships is excellent for analyzing single-ship movements and monitoring all ships within a specific area. However, the AIS data needs to be cleaned, processed, and stored before being usable. This paper presents a system consisting of an efficient and modular ETL process for loading AIS data, as well as a distributed spatial data warehouse storing the trajectories of ships. To efficiently analyze a large set of ships, a raster approach to querying the AIS data is proposed. A spatially partitioned data warehouse with a granularized cell representation and heatmap presentation is designed, developed, and evaluated. Currently the data warehouse stores 312 million kilometers of ship trajectories and more than 8 billion rows in the largest table. It is found that searching the cell representation is faster than searching the trajectory representation. Further, we show that the spatially divided shards enable a consistently good scale-up for both cell and heatmap analytics in large areas, ranging between 354% to 1164% with a 5x increase in workers
Original languageEnglish
Title of host publicationIEEE International Conference on Mobile Data Management
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Publication date2024
Pages211-218
ISBN (Electronic)979-8-3503-7455-1
DOIs
Publication statusPublished - 2024
Event2024 25th IEEE International Conference on Mobile Data Management (MDM): MDM - Brussels, Belgium
Duration: 24 Jul 202427 Jul 2024

Conference

Conference2024 25th IEEE International Conference on Mobile Data Management (MDM)
Country/TerritoryBelgium
CityBrussels
Period24/07/202427/07/2024

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