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Survey on functions, competencies and training needs
Roles: R1 - Marine AI /ML & Big Data Scientist R2 - Marine Big Data Architect / DataSpace & Interoperability Engineer
Sectors: Aquaculture & Fisheries . Ocean Monitoring . Ocean Renewables Port Activities
Primary Sector
*
Aquaculture & Fisheries
Ocean Monitoring
Ocean Renewables
Port Activities
Others
Primary Rol
*
Rol 1: Marine AI / ML & Big DataScientist
Rol 2: Marine Big Data Architect /DataSpace & Interoperability Engineer
Both roles
Type of organisation
*
Research Center / Technology or R&D centre
Small Company (<50 employees)
Medium Company (50–250 employees)
Large Company (>250 employees)
Port Authority
Country
*
Ireland
France
Portugal
Spain
Years of experience
*
0-2 years
3-5 years
6-10 years
> 10 years
Sección 1
Main functions of the role (Marine AI / ML & Big DataScientist).
Rate each function and indicate whether a competency gap exists in your organisation. Rating scale: 1 = Very low · 2 = Low · 3 = Medium · 4 = High · 5 = Very high Gap: Yes / No
*
Rows
Importance
GAP
Gap description (free text)
Analyse
marine data (AIS, satellite, IoT sensors)
1
2
3
4
5
Yes
No
Design predictive models based
on AI / ML for marine applications
1
2
3
4
5
Yes
No
Integrate data from marine IoT
sensors into analytical pipelines
1
2
3
4
5
Yes
No
Develop AI/ML models for marine applications
1
2
3
4
5
Yes
No
Perform anomaly detection and
operational risk analysis in marine systems
1
2
3
4
5
Yes
No
Create dashboards and data visualisations
for technical and non-technical stakeholders
1
2
3
4
5
Yes
No
Apply AI to sustainability,
energy efficiency and marine ESG reporting
1
2
3
4
5
Yes
No
Validate quality, reliability
and integrity of marine datasets
1
2
3
4
5
Yes
No
Collaborate with
multidisciplinary technical, scientific and operational teams
1
2
3
4
5
Yes
No
AI ethics, governance and compliance
1
2
3
4
5
Yes
No
Functions or tasks of role (Marine AI / ML & Big DataScientist) not included in the list above:
Sección 2
Main functions of the role (Marine Big Data Architect / DataSpace & Interoperability Engineer).
Rate each function and indicate whether a competency gap exists in your organisation. Rating scale: 1 = Very low · 2 = Low · 3 = Medium · 4 = High · 5 = Very high Gap: Yes / No
*
Rows
Importance
GAP
Gap description (free text)
Design scalable marine data architectures (data lakes, data meshes)
0
1
2
3
4
5
Yes
No
Design and maintain batch and real-time data pipelines (ETL/ELT)
0
1
2
3
4
5
Yes
No
Integrate heterogeneous marine data
systems
0
1
2
3
4
5
Yes
No
Implement marine interoperability standards (OGC, EMODnet, INSPIRE, SensorThings)
0
1
2
3
4
5
Yes
No
Manage Data Spaces and data-sharing infraestructures
0
1
2
3
4
5
Yes
No
Ensure data governance, quality, lineage and traceability
0
1
2
3
4
5
Yes
No
Design cloud and hybrid solutions for marine environments
0
1
2
3
4
5
Yes
No
Ensure cybersecurity and data protection in marine data systems (NIS2, GDPR)
0
1
2
3
4
5
Yes
No
Real-time data processing architectures
0
1
2
3
4
5
Yes
No
Inter-organisational interoperability and data exchange
0
1
2
3
4
5
Yes
No
Functions or tasks of role (Marine Big Data Architect / DataSpace & Interoperability Engineer) not included in the list above:
Technical competencies
Current level . Required future level . Gap . Training need
For each technical competency, indicate your current level, the level you consider necessary in the next 3 years, whether a gap exists and whether you need training. Scale : 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Python / R — programming for data analysis
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Machine Learning — algorithms, frameworks — Deep Learning — neural networks, computer vision
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data Engineering — ETL, pipelines, orchestration (Airflow)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cloud Computing — AWS, Azure, GCP, cloud architectures
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
IoT & Sensor Data — integration, protocols, platforms (MQTT, FIWARE)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
GIS/Geospatial Analytics — marine spatial data (QGIS, Geoserver)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Real-time Data Processing — Kafka, Spark Streaming, Flink
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
API Design & Integration — REST, GraphQL, OGC APIs
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cybersecurity — security in marine OT/IT systems (NIS2)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data Governance — policies, lineage, data quality — Data Spaces — Digital Twin Ocean
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Interoperability Standards — OGC, INSPIRE, EMODnet, FAIR data
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
AI Ethics & Regulation — AI Act, GDPR applied to AI systems
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional technical competencies not included
Transversal competencies
ESCO classification . Current level . Required future level . Gap
Rate your level in the key transversal competencies identified in the ESCO framework for these roles Scale : 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Technical communication (oral and written, for diverse audience)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Interdisciplinary teamwork with diverse proessional profiles
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Agile project management (Scrum, Kanban, iterative methods)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Technical leadership of data teams
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Technology adaptability and continuous learning
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Innovation and creative thinking applied to marine data
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data-driven decision making
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Sustainability, circular economy and marine environmental awareness
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional transversal competencies not included
Technologies and tools · Current use · Training need
Priority . Format . Duration
Indicate whether you currently use each technology and/or whether you would like to receive training in it.
*
Rows
Currently in use
Would like training
Python (pandas, scikit-learn, NumPy) / R (data analysis and statistics)
TensorFlow / PyTorch (machine learning and deep learning frameworks)
Apache Airflow / Prefect (data pipeline orchestration, ETL/ELT)
Apache Kafka / Spark Streaming / Flink (real-time data processing)
AWS / Azure / GCP (cloud computing platforms and architectures)
FIWARE / NGSI-LD / MQTT (marine IoT and sensor data integration)
QGIS / GeoServer / PostGIS (GIS and marine geospatial analytics)
REST / GraphQL / OGC APIs (API design and data interoperability)
Gaia-X / IDSA connectors (Data Spaces and data-sharing infrastructures)
Copernicus Marine Service / EMODnet / Digital Twin Ocean (marine data portals)
Power BI / Tableau / Grafana (data visualisation and dashboarding)
Docker / Kubernetes (containerisation and deployment of data services)
SQL / NoSQL databases (PostgreSQL, MongoDB, time-series databases)
Data catalogues and lineage tools (FAIR data governance, metadata management)
Cybersecurity and access-control tools for marine OT/IT systems (NIS2 compliance)
Other relevant technologies or tools you use or consider important for these roles:
Training needs
Priority . Format . Duration
Indicate the priority of each training area for your professional development in the next 2 years (1 =no priority · 2= Low . 3= Medium . 4= High . 5 = very high / urgent). *
*
Rows
1
2
3
4
5
AI applied to Blue economy (fisheries, ports, marine renewables)
Advanced Machine LEarning (AutoML, LLMs, foundation models)
Big Data Engineering - scalabale pipelines and architectures
Marine interoperability anda Data Spaces (Gaia-X, IDSA, DTO)
Cloud & Edge Computing for marine environments
Marine IoT and sensor integration (FIWARE, MQTT, LoRaWAN)
Maritime cybersecurity NIS2, OT/IT security)
Data governance and FAIR data principles
AI regulation and ethics (AI Act, GDPR applied)
Advanced marine data visualisation and dashboarding
Agile project management and technical team leadership
Digital Twin Ocean / Copernicus /EMODnet - integration and use
Other training needs, accesss barriers (cost, time, language) or comments
Final remarks
Open space — your expertopinion is especially valuable
Specific gaps or barriers inyour sector (Aquaculture, Ocean Monitoring, Ocean Renewables, Port Activities) not captured in the survey:
Send
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