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==1 Abstract<!-- -->==
 
==1 Abstract<!-- -->==
  
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The project ML-AMAR (Machine Learning Applications in Marine Engineering) aims to develop machine learning tools to optimize the lifecycle management of ships, from design and operation to maintenance and structural monitoring.
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The repository includes two public anonymized datasets generated from the ML-AMAR monitoring campaign. Both datasets have been prepared for scientific and technical distribution by removing sensitive information such as exact coordinates, precise timestamps, vessel/sensor identifiers and individual trajectories.
  
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This document contains the anonymized scientific-technical database from the ML-AMAR monitoring campaign. It has been generated to support the validation of the meteorological forecasting, seakeeping behavior, and life-cycle analysis tools developed within the project. The database integrates inertial signals, GNSS data, and external metoceanographic variables, providing a traceable record of the vessel’s real operational performance along commercial routes.
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The first dataset, ML_AMAR_anonimizacion_version_B_public, contains aggregated information on maritime routes, trip frequencies, departure time slots, trip duration classes, recurrent movement patterns and a non-georeferenced schematic network. It is intended for the analysis of maritime mobility and general route patterns.
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The second dataset, ML_AMAR_positions_1min_metocean_public_B, is derived from the original one-minute monitoring records. It provides aggregated information on operational state, route phase, distance-to-port classes, metocean conditions and vessel dynamic response. It is intended for scientific and technical analyses of the relationship between navigation, waves, wind and vessel behaviour.
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In both cases, the data are published only in aggregated and anonymized form. The repository does not include raw files, real GNSS positions, exact timestamps, operational identifiers or confidential correspondence tables between anonymized codes and real locations. Aggregation, discretization and suppression rules have been applied to prevent the reconstruction of individual trips or specific operational patterns.
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The dataset ML_AMAR_anonimizacion_version_B_public includes aggregated route summaries, trip frequencies, time slot distributions, duration classes, recurrent cycles and a schematic non-georeferenced network. Its main purpose is the analysis of maritime mobility and route patterns.
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The dataset ML_AMAR_positions_1min_metocean_public_B includes aggregated operational states, route phases, distance-to-port classes, vessel motion statistics and metocean conditions. Its main purpose is the scientific and technical analysis of vessel dynamics and metocean forcing.
  
  
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[[Media:Draft_Molina_Sanchez_916438065_3725_ML_AMAR_anonimizacion_version_B_public.xlsx|ML_AMAR_anonimizacion_version_B_public.xlsx]]
 
[[Media:Draft_Molina_Sanchez_916438065_3725_ML_AMAR_anonimizacion_version_B_public.xlsx|ML_AMAR_anonimizacion_version_B_public.xlsx]]
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[[Media:Molina_Sanchez_2026a_6601_ML_AMAR_anonimizacion_version_B_public.zip|ML_AMAR_anonimizacion_version_B_public.zip]]
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[[Media:Molina_Sanchez_2026a_8999_ML_AMAR_positions_1min_metocean_public_B.zip|ML_AMAR_positions_1min_metocean_public_B.zip]]
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[[Media:Molina_Sanchez_2026a_5121_ML_AMAR_positions_1min_metocean_public_B.xlsx|ML_AMAR_positions_1min_metocean_public_B.xlsx]]

Latest revision as of 17:22, 27 May 2026

1 Abstract

The repository includes two public anonymized datasets generated from the ML-AMAR monitoring campaign. Both datasets have been prepared for scientific and technical distribution by removing sensitive information such as exact coordinates, precise timestamps, vessel/sensor identifiers and individual trajectories.

The first dataset, ML_AMAR_anonimizacion_version_B_public, contains aggregated information on maritime routes, trip frequencies, departure time slots, trip duration classes, recurrent movement patterns and a non-georeferenced schematic network. It is intended for the analysis of maritime mobility and general route patterns.

The second dataset, ML_AMAR_positions_1min_metocean_public_B, is derived from the original one-minute monitoring records. It provides aggregated information on operational state, route phase, distance-to-port classes, metocean conditions and vessel dynamic response. It is intended for scientific and technical analyses of the relationship between navigation, waves, wind and vessel behaviour.

In both cases, the data are published only in aggregated and anonymized form. The repository does not include raw files, real GNSS positions, exact timestamps, operational identifiers or confidential correspondence tables between anonymized codes and real locations. Aggregation, discretization and suppression rules have been applied to prevent the reconstruction of individual trips or specific operational patterns.

The dataset ML_AMAR_anonimizacion_version_B_public includes aggregated route summaries, trip frequencies, time slot distributions, duration classes, recurrent cycles and a schematic non-georeferenced network. Its main purpose is the analysis of maritime mobility and route patterns.

The dataset ML_AMAR_positions_1min_metocean_public_B includes aggregated operational states, route phases, distance-to-port classes, vessel motion statistics and metocean conditions. Its main purpose is the scientific and technical analysis of vessel dynamics and metocean forcing.


2 Database

ML_AMAR_anonimizacion_version_B_public.xlsx ML_AMAR_anonimizacion_version_B_public.zip ML_AMAR_positions_1min_metocean_public_B.zip ML_AMAR_positions_1min_metocean_public_B.xlsx

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Published on 27/05/26

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