| CODE | GSC5104 | ||||||||
| TITLE | Marine Data Literacy | ||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||
| MQF LEVEL | 7 | ||||||||
| ECTS CREDITS | 3 | ||||||||
| DEPARTMENT | Geosciences | ||||||||
| DESCRIPTION | This study-unit explores the critical role of data in shaping the digital transformation of marine services to meet stakeholder demands and enhance research and innovation, particularly within areas like Blue Growth and Mission Ocean. Students will learn how data is converted into valuable information and knowledge that is crucial to monitor, manage, and substantially use marine resources. Topics include marine spatial planning, informed decision-making, strategic planning, and policy development. The unit delves into the processes of data extraction and value addition through various downstream services tailored to local user needs. It covers a broad spectrum of data types and sources, including observational and modeled data, and addresses the integration of diverse data forms such as socio-economic and ecological, as well as non-scientific and qualitative data like resource tracking, demography, and performance statistics. The execution of the course is done jointly by the SEA-EU partner universities. Study-unit Aims: This unit is designed to equip students with a comprehensive understanding of the integrated, multidisciplinary assessment and sustainable management of coastal and marine domains. By exploring the extent of the coast, its biological and socio-economic significance, and overarching concepts such as sustainable development and the blue economy, students will grasp how science meets societal needs. The curriculum emphasizes the connection between scientific knowledge and management practices, highlighting how policies and decision-making can be informed by scientific insights. Additionally, the unit aims to provide students with the practical skills essential for visualizing, processing, and analyzing scientific data using professional software. Students will learn to handle various types and formats of met-ocean data, using these in hands-on sessions to identify, understand, and quantify marine ecosystem processes and their temporal and spatial evolutions. They will also become familiar with a range of software packages used for oceanographic and scientific data analysis, learning best practices in data exchange, data management, and the legal principles of data sharing according to FAIR principles and metadata standards. The course includes practical training on accessing and utilizing reliable data sources, such as CMEMS and EMODnet, ensuring students are proficient in using data for applied research and data-based assessments. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - Identify different types and formats of available scientific data; - Demonstrate knowledge of data processing techniques and extract meaningful insights from scientific data; - Apply principles of coastal resource management, mainly Integrated Coastal Zone Management (ICZM), using an ecosystem-based approach; - Assess methods for acquiring relevant data to support decision-making in areas such as fisheries resource assessment and management, water quality monitoring, and evaluating the general health of the sea; - Evaluate and justify the use of data to substantiate theoretical concepts and/or draw scientific conclusions. 2. Skills By the end of the study-unit the student will be able to: - Design and implement feasible sampling and surveying protocols, perform interpretation of data, and derive meaningful conclusions; - Manipulate and manage multiple data sources including models, in-situ instruments, and remote sensing; - Handle different types of data such as time series and gridded data; and work across data formats including ASCII and binary; - Convert between different data formats; - Develop proficiency in data processing and analysis through the use of various software packages; - Identify and utilise available scientific resources effectively; - Apply data processing methodologies to validate scientific theories and/or formulate conclusions based on datasets; - Execute data processing and analysis using software typically employed in oceanographic (and other scientific) research; - Evaluate the data needs of environmental managers to implement coastal zone management using an ecosystem-based approach. Main Text/s and any supplementary readings: - Marine Data Literacy 2.0 available online: https://marinedataliteracy.org/ - European Marine Observation and Data Network (EMODnet) available online: https://emodnet.ec.europa.eu/geoviewer - Copernicus Marine Service available online: https://marine.copernicus.eu/ - European Data Act (this came into force in January 2024) available online: https://commission.europa.eu/index_en - Inspire Directive of the EU on spatial data management available online: https://knowledge-base.inspire.ec.europa.eu/index_en - TRUST principles for databases available online: https://www.academia.edu/ - FAIR data available online: https://www.go-fair.org/fair-principles/ - European Open Science Cloud available online: https://eosc-portal.eu/ |
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| STUDY-UNIT TYPE | Lecture, Independent Study and Practical | ||||||||
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| LECTURER/S | Alan Deidun Adam Gauci |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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