Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.7
2.9
Journals
JMSE
Special Issues
Challenges and Perspectives for Marine Data Science
share announcement

Challenges and Perspectives for Marine Data Science

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 2702

Special Issue Editors

Dr. Angelica Lo Duca

E-Mail Website
Guest Editor
Institute of Informatics and Telematics – National Research Council (IIT-CNR), 56124 Pisa, Italy
Interests: data science; data narrative; web applications; machine learning; cultural heritage; tourism
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Marchetti

E-Mail Website
Guest Editor
Institute of Informatics and Telematics – National Research Council (IIT-CNR), 56124 Pisa, Italy
Interests: open data; data visualization; data science; web applications; cartographic mapping techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Marine research is a multidisciplinary science that involves scientists from different fields, including physics, biology, chemistry, and geology. Over the last few years, new scenarios and perspectives in marine research have been opened along with the development of numerous techniques for the collection of marine data. On the one hand, there are many potentialities given by the huge volume of marine data, including tsunami and disaster warning, prevention, and forecasting. On the other hand, the marine data are also leading to new challenges in data analysis, data visualization, data management, data quality, and data security.

This Special Issue calls for research articles covering novel approaches to marine data collection, analysis, and visualization in relation to marine science and engineering. Conceptual papers describing challenges and perspectives on marine data science are also welcome. Original contributions that report on real experiences and cases in the usage of any kind of data in the marine domain are also encouraged.

While not excluding the possibility of presenting works on other topics regarding marine data science, the specific topics of interest to this Special Issue are the following:

  • Issues, challenges, and solutions related to marine data science
  • Data collection, cleaning, enrichment, integration, and visualization of marine datasets
  • Copyright issues related to the publication and use of collected marine datasets
  • Time series analysis and forecasting related to marine data
  • Machine learning and deep learning analysis of marine data
  • Security and quality issues related to marine data science

Dr. Angelica Lo Duca
Dr. Andrea Marchetti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine science
  • data science
  • data collection
  • data analysis
  • data visualization
  • open data

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 1073 KiB  
Article
On the Non-Gaussianity of Sea Surface Elevations
by Alicia Nieto-Reyes
J. Mar. Sci. Eng. 2022, 10(9), 1303; https://doi.org/10.3390/jmse10091303 - 15 Sep 2022
Viewed by 981
Abstract
The sea surface elevations are generally stated as non-Gaussian processes in the current literature, being considered Gaussian for short periods of relatively low wave heights. The objective here is to study the evolution of the distribution of the sea surface elevation from Gaussian [...] Read more.
The sea surface elevations are generally stated as non-Gaussian processes in the current literature, being considered Gaussian for short periods of relatively low wave heights. The objective here is to study the evolution of the distribution of the sea surface elevation from Gaussian to non-Gaussian as the period of time in which the associated time series is recorded increases. To do this, an empirical study based on the measurements of the buoys in the US coast downloaded at a casual day is performed. This study results in rejecting the null hypothesis of Gaussianity in below 25% of the cases for short periods of time and in over 95% of the cases for long periods of time. The analysis pursued relates to a recent one by the author in which the heights of sea waves are proved to be non-Gaussian. It is similar in that the Gaussianity of the process is studied as a whole and not just of its one-dimensional marginal, as it is common in the literature. It differs, however, in that the analysis of the sea surface elevations is harder from a statistical point of view, as the one-dimensional marginals can be Gaussian, which is observed throughout the study and in that a longitudinal study is performed here. Full article
(This article belongs to the Special Issue Challenges and Perspectives for Marine Data Science)
►▼ Show Figures

Figure 1

13 pages, 4632 KiB  
Article
Towards the Evaluation of Date Time Features in a Ship Route Prediction Model
by Angelica Lo Duca and Andrea Marchetti
J. Mar. Sci. Eng. 2022, 10(8), 1130; https://doi.org/10.3390/jmse10081130 - 17 Aug 2022
Cited by 2 | Viewed by 1152
Abstract
Ship Route Prediction (SRP) is an algorithm that allows assessing the future position of a ship using historical data, extracted from AIS messages. In an SRP task, it is very important to select the set of input features, used to train the model. [...] Read more.
Ship Route Prediction (SRP) is an algorithm that allows assessing the future position of a ship using historical data, extracted from AIS messages. In an SRP task, it is very important to select the set of input features, used to train the model. In this paper, we try to evaluate if time-dependent features are relevant in an SRP model, based on a K-Nearest Neighbor classifier, through a practical experiment. In practice, we build two models, with and without the Date Time features, and for both models, we calculate some performance metrics and the SHAP value. Tests show that although the model with the Date Time features outperforms the other model in terms of evaluation metrics, it does not in the practical experiments. Full article
(This article belongs to the Special Issue Challenges and Perspectives for Marine Data Science)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop