Webinar FAIR Data Principles 2 | Making Marine Data FAIR: FAIR assessment of marine data & information

Webinar FAIR Data Principles 2 | Making Marine Data FAIR: FAIR assessment  of marine data & information
Training Academy event
23 April 2024 16:00–17:45

This webinar is the second in a series of three Blue-Cloud 2026 Training Academy webinars on FAIR* Data Principles.

With input by  EMODnet, Copernicus Marine and several leading marine Research Infrastructures, the Horizon Europe Blue-Cloud initiative developed a collaborative web-based environment that enables open and simplified access to an unprecedented wealth of marine data resources and interoperable tools. In order to implement a technical federation, Blue-Cloud2026 is working with several Blue Data providers towards shared semantic harmonisation for facilitated discovery of blue data and data products. It does so by harmonising and expanding semantic brokerage services interacting Machine-to-Machine with web services and APIs as provided and operated by the Blue Data Infrastructures.

By federating different “blue” Research Infrastructures, Blue-Cloud is contributing to increasing the available data volume and to an easier discovery and access of blue data, open to researchers, industry and society from Europe and beyond to address  issues related to climate change, food, biodiversity conservation, sustainable ocean economy, pollution and natural hazards. This approach is ultimately improving the quality of data available thanks to harmonisation, validation and qualification done in collaboration with the different BDIs, utilising best practices and standards, and assessing  interoperability of the various sources as provided by each federated BDIs.

This webinar will present some of the recent examples of how Blue Data Infrastructures are working towards FAIR assessments and FAIR Implementation Profiles. It will be combined with best practices from projects and initiatives in Europe contributing to M2M semantic interoperability.

Who should attend

Researchers working at Blue data infrastructures and e-infrastructures Research institutes & Academia, Ocean observation, data and modelling institutions.

Access & download the slides from Zenodo

Watch the recording


Tuesday 23 April 2024; 16.00 CEST

Chair: Sara Pittonet Gaiarin, Trust-IT Services and Blue-Cloud Coordinator


Time Session  
16:00 - 16:10

Welcome & introduction

Overview of the Blue-Cloud Data Federation approach

Sara Pittonet Gaiarin, Blue-Cloud Coordinator

Tjerk Krijger - Project engineer at MARIS

Session 1: Blue-Cloud Common Metadata Profile: state of the art from Blue-Cloud federated BDIs

Examples of Blue-Cloud 2026 Data Infrastructures working towards FAIR assessments and FAIR Implementation Profiles for marine data

16:10 - 16:20 Making EurOBIS Biology metadata interoperable with Blue-Cloud VRE Katrina Exter, VLIZ
16:20 - 16:30 EMODnet physics integration with Blue-Cloud Antonio Novellino, ETT
16:30 - 16:40 EuroArgo semantic artefacts Thierry Carval, iFremer

Session 2: M2M Semantic interoperability in Europe

Examples of other initiatives in Europe working on FAIR assessment of marine and earth science data

16:40 - 16:50 FAIR EVA: Bringing institutional multidisciplinary repositories into the FAIR picture Fernando Aguilar Gómez, CSIC -  Spanish National Research Council
16:50 - 17:00 FAIR Connect: Open Access publishing platform of good practices for professional FAIR-Data stewardship Barbara Magagna, GO FAIR Foundation
17:00 - 17:10 Setting up the EarthPortal, the ontology and vocabulary repository dedicated to Earth sciences Guillaume ALVISET, DataTerra
17:10 - 17:20 Insights from EuroGoos Data Management practices Thierry Carval, iFremer
17:20 - 17:45 Q&A, closure and next steps


*About FAIR

The FAIR Guiding Principles for scientific data management and stewardship were first published in Scientific Data, 3:160018 [Wilkinson et al (2016)]. The principles apply to both data and metadata and are: Findable, Accessible, Interoperable, Reusable. They put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. In pursuit of FAIR, there is a need for increased efforts in optimisation, standardisation, best practices and harmonisation across methodologies for ocean data management, applications and digital assets


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