COURSE PROGRAMME

INTRO LECTURES TIME TABLE

Click HERE for virtual sessions (ZOOM link)

Introduction to Marine Data – Alan Deidun

LECTURE 1, Monday 2 March 2026, 5pm – 7pm (Central European Time) View lecture

Key points of the lecture

  • Why do we need marine data?
  • How do we measure and model the sea?
  • Different types of marine data: physical, biogeochemical, ecological; models; observations (in situ + remote)
  • What is operational oceanography?
  • Technologies used to produce marine data
  • Temporal and spatial constraints in data collection and interpretation; how to measure and interpret data avoiding pitfalls
  • The value addition chain of data; downstream services and data product delivery

Reliable oceanographic data sources

Met-ocean data sets: climate, reanalysis, forecast and in situ data

– Alfredo Izquierdo Gonzalez

LECTURE 2, Thursday 5 March 2026, 5pm – 7pm (Central European Time) Download presentation View lecture Key points of the lecture

  • Met-Ocean data types and characteristics
  • Analysis, reanalysis and climatology
  • Data sets uncertainty and accuracy
  • Data sets strengths and limitations
  • Time and space resolution and coverage
  • Overview of some data sets
  • Some CMEMS products description (PHYS and INSITU)
  • Data lexicon: quality information and product user manual

Online Data Portals – Adam Gauci

LECTURE 3, Monday 9 March 2026, 5pm – 7pm (Central European Time) View lecture Download presentation

Key points of the lecture

  • What oceanographic data is freely available? How can this be accessed?
  • Demonstration of professional online data interfaces to visualise in near-real-time ocean data products
  • Portals from where numeric data derived from in-situ measurements, remote sensing, and forecasting models, can be downloaded
  • Demonstration of visualisation software including Panoply, the Sentinel Application Toolbox (SNAP), and QGIS, that can be used to process downloaded data
  • Simple data processing techniques to added-value products (such as colour composites, vegetation and water quality indices, etc…)

Introduction to Operational Modelling – Flávio Martins

LECTURE 4, Thursday 12 March 2026, 5pm – 7pm (Central European Time) View lecture

Key points of the lecture

  • What is a model?
  • Transport of a property: Eulerian vs Lagrangian
  • Discretisation in space and time
  • Model limitations
  • Initial and boundary conditions
  • Downscaling
  • Types of models
  • Operational modelling cycle
  • Data assimilation, analysis and reanalysis
  • Model validation

An introduction to Europe’s in situ open data service by the European Marine Observation Data Network (EMODnet) – Conor Delaney

LECTURE 5, Monday 16  March 2026, 5pm – 7pm, (Central European Time) View lecture

Key points of the lecture

  • Data management tools, principles and technologies deployed by EMODnet
  • DCO Data Sharing, Decade’s Data and Information Strategy and related initiatives
  • Supporting the EU Digital of the Ocean project through faster access to marine data.

Accessing and transforming data – Giuseppe Aulicino

LECTURE 6, Thursday 19 March 2026, 5pm – 7pm (Central European Time) View lecture

Key points of the lecture

  • Brief introduction to web scraping and API
  • Brief introduction to data wrangling
  • Interacting with data servers part 1 (openDAP)
  • Introduction to cloud storage and cloud computing

Fundamentals and examples of marine data analysis – Carlos Román Cascón

LECTURE 7, Monday 23 March 2026, 5pm – 7pm, (Central European Time)

View Lecture

Key points of the lecture

  • Instrumentation and sampling characteristics
  • Data analysis: basic statistics, climatological assessments, anomalies, correlation
  • Spatial analysis of data
  • Time series analysis: Fourier, harmonic, spectral and wavelet analysis
  • Some examples of marine data analysis

Managing and Processing (Big) Scientific Data – Peer Kröger, Daniyal Kazempour

LECTURE 8, Thursday 26 March 2026, 5pm – 7pm, (Central European Time)

View lecture

Key points of the lecture

Managing (Big) Scientific Data

  • IT tools and systems
  • Relational Database Management Systems
    • Data model
    • Basic properties of transactions in RDMS
  • Geo-Information systems
    • Spatial, temporal, and spatio-temporal data models
    • NoSQL Databases
    • Data models
    • Cap-theorem (consistency and availability)

Processing (Big) Scientific Data

  • Data Preprocessing
  • Overview on Distributed Data Processing
    • Hadoop, map-reduce
    • Spark
    • Flink

Introduction to learning algorithms, neural networks and clustering – Hrvoje Kalinić

LECTURE 9, Monday 30 March 2026, 5pm – 7pm (Central European Summer Time)

Key points of the lecture

  • What is unsupervised learning?
  • Distinction between clustering and classification
  • Cluster properties and basic approaches to cluster analysis
  • Examples of some algorithm and applications
  • What is supervised learning?
  • Distinction between classification and regression problem
  • Learning algorithms and why are the introduced
  • Learning as an optimization problem. Gradient descent. Local optimum
  • Linear separability and complexity of neural network architecture
  • Simple (shallow) neural network implementation

Applying AI to Oceanography: case studies – Aleksandra Dudkowska

LECTURE 10, Thursday 02 April 2026, 5pm – 7pm, (Central European Summer Time)

View Lecture

Key points of the lecture

Case studies and demonstration of the different AI/ML models used in Oceanography

Virtual Quiz & Introduction to Physical Mobility in Malta – Adam Gauci

VIRTUAL QUIZ, Monday 13 April 2026, 5pm – 5:30pm (Central European Summer Time)

INTRO TO PRACTICAL SESSIONS, Monday 13 April 2026, 5:30pm – 6:15pm (Central European Summer Time)

Monday 13 April – Virtual Quiz (click here to start)

Thursday 16 April – Virtual Quiz (click here to start)

BIP PRACTICAL SESSIONS

Click here to check the venue
Click here to see the official programme

09:00-09:10 Welcome and official opening

Prof. Alfred J. Vella (Rector, University of Malta)

Prof. Alan Deidun (Rector’s Delegate for SEA-EU, University of Malta)

Prof. Adam Gauci (Course Coordinator, University of Malta)

09:10-12:00 Practical Session 1: Sea-level time series: detecting processes, stationarity and trends Frano Matić, Hrvoje Kalinić, (Alfredo Izquierdo, Daniyal Kazempour)

12:00-13:00 Lunch

13:00-14:15 Practical Session 2: Ocean data visualization and analysis with Ocean Data View (ODV) Aleksandra Cupiał, Daniyal Kazempour, (Jesús Gómez-Enri, Tomás Fernández Montblanc)

09:00-12:00 Practical Session 3: Oil spill modelling Flávio Martins, (Jesús Gómez-Enri, Tomás Fernández Montblanc, Hrvoje Kalinić)

12:00-13:00 Lunch

13:00-16:00 Practical Session 4: Oil spill detection from space with SENTINEL-1 Jesús Gómez-Enri, (Frano Matić, Alfredo Izquierdo, Flávio Martins)

  • 08:00-08:30 – Transfer from Valletta (meeting point) to Sliema Ferries
  • 08:30-09:45 – Boat tour of the Marsamxett and Grand Harbour
  • 09:45-10:30 – Transfer from Rinella to Mdina
  • 10:30-12:00 – Tour of Mdina
  • 12:00-12:30 – Transfer from Mdina to Riviera Beach
  • 12:30-13:00 – Free time at Riviera Beach
  • 13:00-13:30 – Transfer from Golden Sands to Malta National Aquarium
  • 13:30-15:00 – Lunch at La Nave
  • 15:00-17:00 – Tour of the Malta National Aquarium
  • 17:00-17:30 – Transfer from Malta National Aquarium to Valletta

09:00-12:00 Practical Session 5: AI algorithms in oceanography Aleksandra Dudkowska, Frano Matić (Daniyal Kazempour, Aleksandra Cupiał)

12:00-13:00 Lunch

13:00-16:00 Student group work on presentations

09:00-12:00 Practical Session 6: Introduction to sea state and wind wave characterization Tomás Fernández Montblanc, Alfredo Izquierdo, (Flávio Martins, Hrvoje Kalinić, Aleksandra Cupiał)

12:00-13:00 Lunch

13:00-16:00 Student group work on presentations

09:00-11:00 Student presentations and assessment

11:00-12:00 Certificate ceremony

 

Any more questions? Feel free to send us an email!

For more info on the course please follow the details in the course website  or contact us through mdl@sea-eu.org