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FAIR capacity building: growing the network of experts and FAIR-enabled data stations

Updated: May 17

5 NOVEMBER 2024


NETWORK MEETING - SUMMARY


The networking meeting discussed the need for FAIR capacity building to grow the network of experts in FAIR as well as FAIR-enabled data stations. These two go hand in hand. During the meeting there were various presentations from relevant initiatives and organisations contributing to this topic. 


The LACDR explained how they have set up multiple FAIR data implementations by hosting identical datasets across different repositories, including Yoda, a FAIR Data Point, a Desci node, and as Nanopublications in FAIR Connect. This provides the basis for a FAIR data benchmarking environment for applications that produce FAIR (meta)data.


FAIR Solutions focuses on helping organisations to adopt FAIR principles through tailored solutions like a Cloud FAIR Data Point, eLearning platforms, and comprehensive onboarding, ensuring minimal disruption and maximizing data value and reuse.


Hogeschool Leiden offers an accredited FAIR data training course for engineering students, covering technical aspects of FAIR principles and preparing participants for internships, aligning education with practical FAIR data applications.


The GO FAIR Foundation's capacity-building program trains participants in FAIR principles through the "Three-Point FAIRification Framework," combining e-learning, in-person sessions, and fellowships to create a global network of FAIR experts.


DeSci Labs developed a platform to simplify academic publishing, leveraging Blockchain for data integrity and FAIR compliance while enabling seamless linking of publications, data, and metadata for long-term preservation and reuse.


Leiden Academic Centre for Drug Research (LACDR) - FAIR Orchestration Demonstration and Benchmarking

Contact - Erik Schultes: eriks@gofair.foundation



The LACDR is involved in a project called "Staying Ahead of the Virus," focusing on leveraging Dutch supercomputers to predict structural features of the COVID-19 spike protein using virtual protein sequences. The data resulting from this project was then hosted on different repositories, each adhering to FAIR principles but using different approaches.


Key implementations include a parallel setup: one using Yoda (an iRODS-based application), one employing a FAIR Data Point, one on a Desci node and one publishing the data as free Nanopublications in FAIR Connect. These systems thus host identical datasets with matching metadata, enabling comparisons of FAIR compliance and interoperability. 


This infrastructure serves as a demonstration platform, showcasing varied FAIR implementations to help users assess suitability for their needs. The team aims to refine FAIR practices and create benchmarks for applications, offering a practical, technology-agnostic approach to data management while fostering scalability and innovation in FAIR data usage.




FAIR Solutions - Enabling FAIR for You

Contact - Wouter Franke: wfranke@fairdatasolutions.com


FAIR Solutions, founded in 2020, focuses on enabling organizations to adopt and implement FAIR data practices to maximize the value and reuse of their data. Their services include providing a non-invasive, open-source Cloud FAIR Data Point, designing tailored FAIR solutions based on organizational needs, and offering comprehensive onboarding to ensure broad adoption across business, IT, and end-user levels. They also provide an extensive eLearning platform with modules ranging from basic to advanced, accelerating the adoption of FAIR principles. With a focus on minimal disruption and maximum impact, FAIR Solutions helps organizations integrate FAIR principles into their operations.



Hogeschool Leiden - FAIR Data Engineering Course

Contact - Herman van Hagen: haagen.van.h@hsleiden.nl



The Hogeschool Leiden provides a FAIR data training course for engineering students with 60 participants enrolled. The course, accredited by the institution, emphasizes technical aspects of FAIR principles, including Semantic Web technologies, data exchange formats, ontologies, controlled vocabularies, federated queries, metadata standards like Dublin Core and DCAT, licensing, and provenance. Students will also be introduced to FAIR-enabling tools and knowledge discovery applications.


The program aims to prepare students for internships in September 2025, providing practical opportunities for companies to host skilled interns. The students' backgrounds are primarily in IT-related fields such as software engineering, hardware design, and data management. Hogeschool Leiden encourage companies to express interest in hosting interns and offer contact details for coordination. The program seeks to align with broader FAIR initiatives and provide practical, hands-on experience.




GO FAIR Foundation - The GO FAIR Foundation Capacity Building Program

Contact - Barbara Magagna: barbara@gofair.foundation



The GO FAIR Foundation has developed a capacity-building and fellowship programme focused on FAIR data principles. Central to the program is the "Three-Point FAIRification Framework," which includes FAIR Awareness, FAIR Implementation Profiles (FIPs), Metadata for Machines (M4Ms) and FAIR Orchestration. Participants learn to use FAIR-enabling resources, develop machine-readable metadata, and deploy FAIR-supporting infrastructures. The program offers modules at three levels: implementer (hands-on application), facilitator (guiding communities), and trainer (mentoring others).


Training involves a combination of e-learning, in-person sessions, hackathons, and one-on-one coaching, requiring up to 200 hours depending on prior knowledge. Successful participants receive qualifications and recognition on the GO FAIR Foundation website. Additionally, the fellowship programme supports up to 20 fellows annually, providing 250 hours of interaction to develop expertise and collaborate on FAIR projects. The initiative aims to create a global network of FAIR experts equipped to implement and promote FAIR data practices effectively.




DeSci Labs - Empowering Researchers from Data to Publication

Contact - Leonie Raijmakers: leonie@desci.com



This presentation highlights the Desci Laba platform designed to simplify academic publishing. The platform enables seamless linking of publications, data, and metadata to ensure long-term preservation, replication, and interoperability. It leverages Blockchain technology for stable and persistent identifiers, ensuring data integrity over time. Users can upload manuscripts, datasets, and associated metadata easily, with automated tools for generating abstracts and linking authors to ORCID profiles.


The platform aims to prevent data silos, enabling transparent updates and versioning without overwriting past versions. It also supports restricted data access through secure systems, ensuring ethical use of sensitive information. By integrating DOIs and encouraging dataset recognition, the system promotes proper attribution and reuse of data. This approach aligns with broader academic goals of fostering collaboration, reproducibility, and FAIR compliance while addressing challenges in linking data to publications and making them accessible for future research.








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