Search

This article assesses the difference between the concepts of ‘open data’ and ‘FAIR data’ in data management. FAIR data is understood as data that complies with the FAIR Guidelines—data that is Findable, Accessible, Interoperable and Reusable—while open data was born out of awareness of the need to democratise data by improving its accessibility, based on the idea that data should not have limitations that prevent people from using it. This study compared FAIR data with open data by analysing relevant documents using a coding analysis with conceptual labels based on Kingdon's theory of agenda setting. The study found that in relation to FAIR data the problem stream focuses on the complexity of data collected for research, while open data primarily emphasises giving the public access to non-confidential data. In the policy stream, the two concepts share common standpoints in terms of making data available and reusable, although different approaches are adopted in practice to accomplish these goals. In the politics stream, stakeholders with different objectives support FAIR data and from those who support open data.

This upload contains the report on piloting the application of a controlled vocabulary to REPOPSI, the open repository for research data hosted on the Open Science Framework (OSF)platform. The goal was to improve the Repository’s adherence to the FAIR principles (especially Interoperability and Reusability) by putting the REPOPSI metadata values into a machine-readable format and implementing a FAIR-compliant controlled vocabulary. The Python code to generate XML metadata documents in compliance with the latest version of the DataCite Metadata Schema (Version 4.4) is available at https://doi.org/10.5281/zenodo.8150869

This deliverable pertains to task 9.3, which is dedicated to the establishment of data standards for SARS-CoV-2 variants and lineages. It plays a crucial role in the development of a network of specialised data experts in SARS-CoV-2 genomic surveillance, contributing to the objectives of WP1 and WP8. Furthermore, it aligns with WP2, focusing on training and capacity building initiatives. The accomplished work encompasses a workshop centred around the Fair Data Point concept, exploring its potential in advancing the goals of WP9. Additionally, a workshop addressing SARS-CoV-2 data standards was conducted, covering essential aspects such as metadata standards and variant/lineage nomenclature. A dedicated data standards task force was formed, which conducted a comprehensive survey to gauge the adoption of the proposed standards among participating countries within CONVERGE WP9. Furthermore, a separate task force dedicated to pathogen genomics data management collaborated with other projects, contributing to the development of valuable resources aimed at facilitating efficient data sharing. Overall, these endeavours represent significant progress in the establishment of robust data standards and effective data management practices within the project, ultimately contributing to enhanced genomic surveillance of SARS-CoV-2. Regarding variant and lineage nomenclature, Nextclade and Pangolin are widely adopted tools for variant classification. Integrating both tools in a comprehensive data hub allows for a thorough understanding of the genetic diversity of SARS-CoV-2. The data standards task force compared the metadata requirements of GISAID, ENA, and PHA4GE, revealing differences in the number and specificity of fields. The comparison showed that PHA4GE had the most comprehensive set of fields, while GISAID and ENA had unique fields specific to their databases. Harmonising metadata specifications and promoting interoperability remain essential challenges. The survey on metadata availability and public accessibility highlighted disparities among countries, emphasising the need for standardised metadata across the network.

FAIRification of aviation vocabularies: Data Management Plan (DMP) 0.1.2a: Alpha version based on FioDMP (Fiocruz) model, Alpha version based on FioDMP (Fiocruz) model

This document provides an assessment of the progress from 2020-2023 in developing FAIR data policies within ENVRI-FAIR environmental research infrastructures. In particular, it is a comparison with D4.2 which provided the initial landscape survey is given. The text describes the progress made in advancing ENVRI research infrastructures towards FAIRness, and the diagrams provide ‘heat maps’ where the colour indicates the state. The conclusion is that much progress has been achieved, but – as always – there is more that could be done, with varying amounts to be done in the different RIs. It is of particular importance that progress on the ‘legal policies’ has been rapid and is almost completed for the RIs of ENVRI.

This presentation is from the FAIR-EASE webinar heldon 12 July 2023, 15:00-16:00 CEST.FAIR-EASE discussedthe transformative journey from a 'data lake' to a dynamic 'data space.' Furthermore, the webinar presented a modern web-based perspective on this architecture, where the FAIR-EASE team's vision has been shaped by both the project's unique challenges and the insights derived from computer science research. It explored innovative approaches to federated queries on a distributed knowledge graph. Additionally,the webinar discussed Examind, and dove into a talk centered around geospatial interoperability. The meetingspurpose was to involve external communities, share the FAIR-EASEvision and objectives, and receive feedback.

FAIR-by-design NFFA case study within Module 3 of the course "News and insights from Open Science, and how to exploit them in your scientific work" held for MSCA-ITN SMART-X, held on 11 July 2023. This presentation focus on the implementation of Open Science and FAIR principles in a Scanning tunneling microscopy (STM) laboratory at CNR-IOM.

A brief demonstration and explanation of the developed functionalities and their role within the wider WCO data ecosystem., Presented at the NERC Digital Gathering, British Antarctic Survey (BAS), Cambridge, UK. 10th - 11th July 2023.

This presentation is given during theRDA – SciELO 25 Years Seminar,Open Science Modus Operandi of Research Communication Title:The FAIR Data Maturity Model: RDA recommendations for FAIR assessment methods for all disciplines (website) Description:The importance of FAIR data is recognized worldwide. In this lecture we share the effort to ensure that FAIR dataset assessments developed for specific research communities are aligning to common recommendations. A critical element of research are the data used to determine the findings published in an article. These data along with the methods and software used, are valuable contributions to the scientific record. The broad research community has been working to improve the description, preservation and sharing of these digital objects so that they can be indexed, associated with the paper and creators, and potentially reused in future research. The FAIR Guiding Principles, published in 2016, initiated a moment of convergence across different disciplines motivating the development of assessment methods for researchers to use in order to ensure their data are FAIR – findable, accessible, interoperable, and reusable. The many data assessment methods were mostly unique to their community and not comparable across communities. As the number of assessment methods increased, members of the RDA felt it necessary to establish a “maturity model” that could be used to guide new assessment methods as well as compare current methods. In this lecture, co-chairs Shelley Stall and Edit Herczog, will give a brief history of the FAIR Data Maturity Model Working Group activities and provide an overview of the model elements. Resources mentioned during the presentation: RDA FAIR Data Maturity Model Working Group:https://www.rd-alliance.org/groups/fair-data-maturity-model-wg FAIR Data Maturity Model Recommendation:FAIR Data Maturity Model Working Group. (2020). FAIR Data Maturity Model. Specification and Guidelines (1.0). https://doi.org/10.15497/rda00050 Publication highlighting the FAIR Data Maturity Model Recommendation:Bahim, C., Casorrán-Amilburu, C., Dekkers, M., Herczog, E., Loozen, N., Repanas, K., Russell, K. and Stall, S., 2020. The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments. Data Science Journal, 19(1), p.41.DOI: https://doi.org/10.5334/dsj-2020-041 FAIR Guiding Principles:Wilkinson, M., Dumontier, M., Aalbersberg, I.et al.The FAIR Guiding Principles for scientific data management and stewardship.Sci Data3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 Detailed Description of Use Cases originally presented during an RDA Webinar: RDA FAIR Data Maturity Model- Aligning International Initiatives for Promoting & Assessing FAIR Data This webinar convened a group of experts representing national science organizations to discuss their current initiatives to enhance the FAIRness of the science within their communities applying different approaches and the use of the FAIR Data Maturity Model as a framework for comparing results. Video:https://youtu.be/rIMfwu7-hes Your Journey to Open Science - checklists and guidelines for researchers and research teams to start their open science practices English Portuguese Spanish

This deliverable provides an overview of relevant developments in the practices and technologies that support making research assets findable, accessible, interoperable, and reusable, especially where these are relevant for the ENVRI cluster of environmental research infrastructures. A review of selected initiatives and associated technologies is provided with some context for their relevance to the ENVRI community, especially those that are represented within the ENVRI-FAIR consortium.

The key scientific output of the EATRIS-Plus project is to develop a Multi-omic Toolbox available for researchers in order to have a better understanding of the molecular profiles in personalised medicine. Within work packages 1, 2, and 3, we implement practices based on the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles to ensure reproducibility of our work and to make the multi-omics cohort data reusable for future translational research. The aim of this deliverable (D2.2) is to describe methods developed and applied to the Czech multi-omics cohort 1 that can improve comparability of data when integrating omics data from different sources. Integration of omics data from different sources can be challenging when data and data processing steps are not sufficiently annotated, or sources of biological and technical variation are unknown. The Czech multi-omics demonstrator cohort serves as a demonstrator for the development and application of computational workflows for omics preprocessing and integrative analyses. &nbsp

This webinar was organised to help project coordinators, researchers and research support staff on the European Commission's requirements for Open Science.Requirements forOpen Access to scientific publications andResearch Data Management are presented, not only during and after the project butas wellat the grant proposal stage. An overview of the European Commission's publishing platform - Open Research Europe - was also presented, along some other useful tools such as Argos (Data Management Plan), Amnesia (data anonymisation), OpenAIRE Explore, etc. Learn about: Mandatory and recommended Open Science requirements in Horizon Europe (HE) Compliance with the HE Open Access to publications mandate Managing and sharing Research Data in HE projects Delivering Data Management Plans and reporting publications and datasets in HE OpenAIRE tools and services to support HE projects Target audience:project coordinators, researchers, research managers, librarians and data stewards. Recordings:https://youtu.be/hq9e6cvFHpY (03/07/2023 session),https://youtu.be/lr082NR71_M (16/03/2023 session),https://youtu.be/_tVfaYGE8vg(22/11/2022 session)

This paper presents a digital resources ecosystem prototype of integrated tools and resources to support heritage-led regeneration of rural regions, thanks to a deeper understanding of the complexity of cultural natural landscapes throughout their historical and current development. The ecosystem is conceived as a distributed software platform establishing data ecosystem and open standards for the management of information, aimed at providing different services and applications to address the needs of the various end-users identified. The platform has been conceived and realised in the framework of a Horizon 2020 research project, with a view to building a set of holistic knowledge about rural regions and their cultural and natural heritage and making it available for long-lasting heritage-led territorial processes of change. It is the product of a multidisciplinary collaboration amongst heritage, digital humanities and ICTs ex- perts, and combines data and methodologies from a range of approaches to humanities together with the customisation of effective digital tools. It has been designed for deployment also in cloud systems compli- ant with the Infrastructure-as-a-Service paradigm. All data is Findable, Accessible, Interoperable, Reusable (FAIR data). It hosts and integrates different tools, making the data gathered with/for local stakeholders usable and making the same data re-usable within the tools’ functions, generating integrated heritage knowledge. It comprises data on 19 rural pilot territories, where the tools and their integration have been developed and tested, while 62 more are partially included as additional territories which partici- pate in certain activities within the project. The main testers for this platform and its functions are the local stakeholders of these territories. The paper describes and analyses the platform and its impact, dis- cussing the integration of tools as an innovative approach that goes beyond the use of individual tools in shaping a multidimensional vision. It also offers an analysis of the potential of an integrated digital ecosystem in evidence-based and place-based regeneration strategies. Some reflections for developments and cooperation during the pandemic are also presented.

This Deliverable provides an assessment of the level of FAIRness of the seven RIs in the Biodiversity and Ecosystem subdomain. The assessment has been done by taking advantage of the FAIR Implementation Profiles, resulting from the collaborative effort between the GO-FAIR Foundation and ENVRI-FAIR WP5. In this report the outcome for the FIPs compiled by the RIs belonging to WP11 is discussed in more detail. A final chapter is dedicated to the evolution of the FIPs along the four years of the project.

The ENVRI landscape report for National Stakeholders summarizes the outcomes of the interviews that were conducted with five different national stakeholders within the environmental domain in Europe. The report addresses awareness of the ENVRI work and activities in different countries and particularly the ways the national ENVRIs are organized and coordinated currently. Most importantly, the report sums up how countries see the significance of aligning national strategies with the strategies at European level, and what are the related challenges and means of improving the alignment.

This is the final deliverable of WP6, the training and capacity building work package of ENVRI-FAIR. The objectives of WP6 were to provide training to ENVRIs and key ENVRI stakeholder groups about the FAIR principles, how to implement these in practice in RI services and data management activities at data centre level, how to evaluate the degree of implementation using FAIR metrics, as well as relevant legal and policy requirements. This deliverable report summarises the activities we have undertaken, with special focus on the preparation and running of training events aimed at the ENVRIs’ data centre staff. We also describe the infrastructure that was developed to provide a comprehensive Learning Environment for the ENVRI Community, including a catalogue, learning platform and repository and the Training Gateway component of the ENVRI-Hub. Finally, the report also contains an extensive discussion of “lessons learned” that we hope will be of use for future ENVRI Community training activities.

The overarching goal of ENVRI-FAIR is for all participating RIs to improve their FAIRness and prepare the connection of their data repositories and services to the European Open Science Cloud. This deliverable reports the efforts Task 7.3 contributed to the development of common FAIRness goals in the second half of the project. The objective of this task is to provide co-development support driven by an implementation plan that identified by each subdomain, joint use cases among RIs or subdomains, and other needs identified during the project. In the second half of the project, Task 7.3 focused on the support for the integration with ENVRI-Hub, testing and validation of the developed services by subdomains, and exploitation and knowledge transfer.

Two presentation slide decks from WorldFAIR webinar, 'FAIR Implementation Profiles, the Cross-Domain Interoperability Framework and the WorldFAIR Methodology' on 28 June 2023. WorldFAIR is a coordinated and broad-based effort to explore the realities of FAIR implementation across a large range of different research domains and important cross-domain research areas. The FAIR principles rely on standards to describe data and metadata, and if the promise of FAIR is to be achieved, these standards must be agreed and adopted both within and across domains. The methodology used in WorldFAIR employs FAIR Implementation Profiles (FIPs) and other techniques for understanding what resources enable FAIR within each of the domain Case Studies in the project. This input is then considered by a group of standards experts in light of common standards which can be used universally, cutting across domain boundaries. The emerging result is a metadata ‘lingua franca’, designed to support a number of critical functions in the realisation of FAIR across domains: the Cross-Domain Interoperability Framework (CDIF). The CDIF is a set of recommended, existing standards and implementation approaches which builds on identified domain practice to support key functions, including resource discovery, access to controlled data, and integration and reuse of data from disparate sources. Designed to support machine-actionability to the greatest possible extent, CDIF can be adopted progressively, building on the FAIR-enabling resources and standards identified by the Case Studies for their domains. The coordination and synthesis activity in WorldFAIR (Work Package 2) will produce a draft of the CDIF recommendations, but will also document other significant findings from this analysis: how can ‘domain-sensitive’ FAIR assessment really be carried out in practice? What issues emerge as the most important for enabling FAIR, both within and across domains, and what policy measures can be taken to support FAIR implementation into the future? Ultimately, this impacts the necessary culture around data management, emphasising the need for more granular data description and richer metadata describing data provenance and processing. This webinar describes the methodology developed by WorldFAIR for performing this analysis, and summarises the findings, in terms of the initial assessment with FIPs, and covering the work-to-date on the development of the CDIF recommendations. Emerging policy implications and impacts on data management practice are also described. The programme for the webinar is as follows: WorldFAIR’s use of FAIR Implementation Profiles (FIPs) (Simon Hodson) What is a FIP? The role of FIPs fit in the WorldFAIR Methodology How WorldFAIR Case Studies have been using FIPs What we learnt? Findings and recommendations FIPs and the Cross-Domain Implementation Framework (Arofan Gregory) CDIF CDIF as a ‘lingua franca’ (what it is, and what it is not) FIPs and CDIF as a basis for domain-sensitive FAIR assessment Publishing FIPs and alignment Accompanying the webinar, the following resources may be of interest: FAIR Implementation Profiles (FIPs) in WorldFAIR: What Have We Learnt? (D2.1): https://doi.org/10.5281/zenodo.7378109 First WorldFAIR Policy Brief (D1.3): https://doi.org/10.5281/zenodo.7853170 Presentations from the WorldFAIR CDIF workshop at the RDA Plenary on 20 March: https://worldfair-project.eu/2023/03/22/the-worldfair-projects-cross-domain-interoperability-framework-2/ Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393. &nbsp

This document presents the policies planned for the ENVRI-Hub service catalogue within the context of interoperation with EOSC and the FAIR principles. The ENVRI-Hub catalogue is supplied by the Research Infrastructures within ENVRI-FAIR (or more specifically their digital asset suppliers) and so it is necessary for the policies of the RIs to be sufficiently compatible to avoid problems of conflicting policies when accessing digital assets at the RIs from the ENVRI-Hub. The key policy drivers (EOSC Rules of participation, FAIR principles, and ENVRI-Hub initial documents) were documented in D4.6 where policy recommendations for the RIs were made, in order for their policies to be compatible with ENVRI-Hub and hence EOSC and FAIR. The next steps to create policies for the ENVRI-Hub were also documented in D4.6 following ENVRI-FAIR Policy workshop 4 where the approach was discussed. While ENVRI RIs are finalising their policies and their implementation through guidelines (best practice) and IT implementation (technology) this deliverable lays out the policies needed at ENVRI-Hub and the steps to realisation.

The ENVRI-FAIR project activities have clearly improved the FAIRness of the data collected by the Ecosystem and Biodiversity RIs and the level of cross-RI collaboration. With a long-term plan, the RIs must have also a trajectory in terms of long-term collaboration, consolidation and management that should be also based on the experience in ENVRI-FAIR. In this deliverable an analysis of the possible common development paths, complementarities and specific long-term use cases are presented and prepared for a discussion among the RIs’ legal entities.

The report summarises the collaboration between the environmental research infrastructures cluster and other ESFRI clusters during the conduction of the project.

The overarching goal of ENVRI-FAIR is for all participating RIs to improve their FAIRness and prepare the connection of their data repositories and services to the European Open Science Cloud. With the development of FAIR implementations from the participating RIs and integrated services among the environmental subdomains, these data and services will be brought together at a higher level (for the entire cluster), providing more efficient services for researchers and policy makers. This deliverable presents new developments to the knowledge base, initially presented in the ENVRI-FAIR Deliverable 7.3. The new developments focus on the knowledge base search engine. We introduce a new automated pipeline to index online resources: web pages, datasets, and computational notebooks. We also present a complete redesign of the search engine and interface. These new features were deployed in a cloud environment, making the service more performant and reliable. We also discuss the integration with the ENVRI community through the ENVRI-Hub and show a demonstration of the new search engine. By allowing users to find resources from ENVRI and its RIs, the knowledge base search engine improves interoperability.

D4.3 Report on legal and IPR aspects of service policies in the ENVRI domain describes the policy issues facing ENVRI RIs and in particular the state of plan and plans for progress. The deliverable relies on earlier deliverables, particularly D4.2 which provided the landscape analysis and the ongoing D4.5 updating the policy landscape together with the policy aspects of external development of FAIR services in the deliverable D4.4. It also benefits from the work done on methods for generating policy and maintaining policy consistency both with external factors (e.g., legislation) and the requirements and constraints of individual RIs to be reported in D4.6 and D4.7. The co-evolution of policy among the ENVRI RIs is as essential to interoperability as the technical co-evolution managed in WP5 and WP7, together with the individual ENVRI subdomains in WP8, 9,10 and 11.

The BEERi activity report summarizes the activities of the Board of European Environmental Research Infrastructure within the lifetime of the ENVRI-FAIR project. It provides an overview of the main common topics tackled within the BEERi and taken actions regarding them, illustrating the cooperation of the Community of the environmental RIs.

The ENVRI-Hub design study contains the analysis of the technical preconditions for the successful implementation of the design ENVRI-Hub as a centralised access interface to environmental data and services building upon the increase of FAIRness achieved in the ENVRI-FAIR project; it will be based on the validation results from WP7 and Task T5.4, and the achievements in the subdomain implementation work packages WP8-11 of this project. The design of the ENVRI-Hub started as a multifaceted initiative that brought together engineers, scientists, and managers to create a collaborative platform for environmental research and innovation, aiming at advancing environmental research in Europe. As a web platform, the ENVRI-Hub can provide access to environmental data and services offered by the European environmental Research Infrastructures. The data and services provided by the ENVRIs cover four domains of the Earth system, Atmosphere, Ocean, Solid Earth, and Biodiversity-Ecosystems. The ENVRI-Hub intends to facilitate multi-and-inter-disciplinary environmental research by making the data and services interoperable across the domains and easy to use by anyone in the ENVRI community. From different perspectives, depending on the role and interest of the user, the ENVRI-Hub encompasses various aspects, including technical considerations, scientific content, usability, and strategic management. This document describes the process of designing the ENVRI-Hub during the ENVRI-FAIR project, highlighting the key challenges and achievements as well as the potential of an operational ENVRI-Hub in the future.

In this deliverable we produce a list of services developed by Biodiversity and Ecosystems subdomain RIs. The services we considered were developed or utilised during the ENVRI-FAIR project in order to increase the interoperability and the co-development of service among different RIs of the subdomain.

BY-COVID Work Package (WP) 2 brings together datasets and catalogues of metadata across domains, assesses data governance and access procedures, and contributes to increase the FAIRness level of different data sources. It aims to align metadata descriptions and other semantic information, first within domains (e.g., biomolecular and imaging, clinical and health, survey, etc), and in a second stage (in alignment with WP3 developments) across domains to propose a reference catalogue with harmonised metadata descriptions, which can facilitate data access and eventually enable data mobilisation for the analysis workflows specified by WP4 . Deliverable 2.2 (D2.2) focuses on data access and transfer across research domains and jurisdictions. Originally intended to address technical, legal, and organisational barriers in data sources, its scope expanded to include all types of data that also link to pathogen variants via SARS-CoV-2 DataHubs (WP1). The objectives of D2.2 are two-fold: ensuring compliance with data privacy principles for controlled access data and proposing strategies to enhance data interoperability. Efforts included developing a survey, conducting ad-hoc meetings with key stakeholders, and aligning with the FAIR data principles. The deliverable contributes to ongoing efforts to facilitate efficient and responsible data sharing, which should enable faster and coordinated responses in future pandemics.

This deliverable showcases the progress and demonstrators of services integration between the ESFRI Cluster of Environmental Research Infrastructures and the European Open Science Cloud. It highlights the successful onboarding of the ENVRI Catalogue of Services onto the EOSC Marketplace, improving visibility and accessibility. Ongoing discussions with OpenAIRE aim to enhance the discoverability of ENVRI digital assets within EOSC. The document emphasises the importance of harmonisation, interoperability, and collaboration in achieving seamless integration and maximising the impact of environmental research infrastructures.

The collection of Fotopersbureau De Boer (Noord-Hollands Archief) is particularly notable for its abundance of subjects and size. It contains valuable material for research on current topics such as environment, energy, and social inequality, and provides a glimpse into the everyday lives of people. Although the collection is accessible at the archive's website, it cannot easily be used due to its lack of standardisation and the omission of external references. This project will enrich the metadata of the collection by linking them to thesauri of locations, persons, and keywords in order to further open up the collection for use in research and the cultural heritage sector. This newly added information will be stored back into the collection management system of the archive for sustainable storage. When completed, the project delivers a download of all the curated and enriched metadata as spreadsheet (CSV), as well as Linked Open Data (RDF). This poster was presented at the CLARIAH Tech & Data Day, June 29, 2023., This project is a collaboration between the University of Amsterdam (UvA) and the Noord-Hollands Archief (NHA). The research for this poster was made possible by the CLARIAH-PLUS project financed by NWO (Grant 184.034.023)

Presentation slides "Sharing research data and software - FAIR & FAIR4RS" for the Collaborative scientific software development summer school hosted by University of Bergen Library Digital Lab. Open Science – a paradigm shift Sharing data: Open & FAIR research data Sharing software/code: FAIR for research software How to make your code citable, Contact: research-data[at]uib.no

Presentation for the Amsterdam UMCTutorial series: Open Science and FAIR data //RonaldCornet (APH Digital Health) and Mariska Leeflang (APH Methodology) FAIR session 3: review your data, June27, 2023 - part:With a little help from my friends:FAIRificationworkflow: Makingdata FAIR in practiceand ready for the Health-RI infrastructure Health RI, Mijke Jetten (on behalf ofJolanda Strubel,Sander de Ridder, Bruna dos Santos Vieira)

Presentation slides "Sharing research data and software - FAIR & FAIR4RS" for the Collaborative scientific software development summer school hosted by University of Bergen Library Digital Lab. Open Science – a paradigm shift Sharing data: Open & FAIR research data Sharing software/code: FAIR for research software How to make your code citable

D10.5 “Final Report on Implementation Activities” describes the work towards making the RIs in the solid Earth subdomain FAIR in terms of FAIRness of the assets and EOSC-interoperability. In this deliverable we therefore describe for each WP10 task, the work done to address the gaps identified by Deliverable “D10.2 Roadmap for implementation of FAIR concepts”, prioritised and harmonised in D10.3 “D10.3 Report on coordination, prioritisation, and harmonisation in the Solid Earth Subdomain”.

The deliverable "D10.3 Report on Coordination, Prioritization, and Harmonisation in the Solid Earth Subdomain," primarily focuses on the strategic prioritization of activities aimed at enhancing the application of FAIR (Findability, Accessibility, Interoperability, and Reusability) principles across various Earth Science disciplines in WP10. This document provides an overview of the selected activities, explaining their prioritization based on the gap analysis and need for improvement in FAIRness. The report reflects upon the efforts of the European Plate Observing System community in embedding FAIR principles from the outset and further improving its commitment through these prioritized activities. Key initiatives include the harmonisation of metadata, implementation of Persistent Identifier systems, data and metadata lifecycle management, and the development of common vocabularies across multiple Earth Science domains. The success of these activities highlights the importance of strategic planning and prioritization in enhancing FAIRness and overall data management effectiveness in the ENVRI community.

This document outlines the training activities that have been completed since the beginning of the grant and their impact. The EOSC-Life training programme is built on the training needs analysis, which was presented in D9.1 Final report of analysis of the training needs of different EOSC-Life users in month 12. EOSC-Life training is aimed at two target communities that have distinct needs and different roles towards establishing a European Open Science Cloud (EOSC): (i) the Research Infrastructures (data) staff and (ii) the end-user of the (data) services offered. The deliverable gives an overview on the wide range of training offers completed, which highlight that EOSC-Life managed extremely well to ensure cross WP involvement and adapted the training to remote offers during the pandemic restrictions. Since the training activities described in D9.2 Review of EOSC-Life training activities, their impact and potential adaptations, our focus has been on developing and publishing the e-learning materials, while activities around courses, workshops and open calls continued. In total, since the beginning of the project we have supported over 1000 participants with in-person/virtual training and over 6000 participants with e-learning. Training in EOSC-Life has been organised in a top-down as well as bottom-up approach; top-down training activities have been organised by the technical work packages in EOSC-Life as well as the training work package, while the Training Open Call process allows for training activities organised by the EOSC-Life community to receive EOSC-Life support. All training activities relate to the needs analysis. Three rounds of the Training Open Call have been completed, in total we received 22 applications and 15 proposals received funding. In conclusion, EOSC-Life training activities were a driver and sustainer of the EOSC-Life community and an important pillar in reaching external audiences.&nbsp

The Deliverable "D5.4 ENVRI Service Catalogue" presents the development, implementation, and operation of a comprehensive service catalogue within the context of the ENVRI-FAIR project. The deliverable outlines the creation of a FAIR compliant and EOSC-ready catalogue, primarily focusing on services providing access to data. The innovative design and implementation of the catalogue embrace the adoption of rich metadata standards for ingestion and storage, namely EPOS-DCAT-AP metadata profile and the CERIF model, facilitating the description of diverse services across different research infrastructures (RIs). The validation processes, including service validation at the subdomain level, FAIRness evaluation, and an implementation phase, ensure the robustness, accuracy, and FAIR compliance of the catalogue, promoting its interoperability with the EOSC catalogue. The deliverable further details the operation of the catalogue, which involves a harmonised effort among service providers, backend developers, and front-end developers. It underscores the ongoing endeavour to ingest more metadata records, provide support for metadata curation, and work towards semantic interoperability. Future work, as outlined in the deliverable, involves enhancing the catalogue's operation by improving metadata quality, enhancing semantic interoperability, and adapting to the diversity of service types from different RIs. The ENVRI Service Catalogue represents a pivotal step towards advancing FAIR practices in environmental research. Its development, implementation, and operation symbolise an ongoing commitment to continuous improvement, adaptation, and learning, with the ultimate goal of propelling environmental research towards new horizons of discovery and innovation. By aligning with the EOSC catalogue requirements, it envisions a broader, more integrated network of scientific resources, thus empowering global researchers. The ENVRI Service Catalogue, as the embodiment of the ENVRI-FAIR project's vision, promises to facilitate open, FAIR, and efficient access to services and data in the environmental research domain.

DANS has been working on migrating from our old archiving system to new Data Stations based on Dataverse technology. On June 12th 2023, we held an online event to present the DANS Data Stations. The event was announced as follows: Showcase DANS Data Stations On Monday 12 June, we will present our Data Stations. We will show you how to deposit your dataset and how to find datasets for reuse. Data stewards and researchers can digitally archive their datasets themselves in our new domain-specific repositories: secure, findable and equipped with essential information.Ease of use is key in these new data services. The Data Stations offer more options for editing and reusing datasets. For instance, you can add new versions to an existing dataset. You can also view PDFs, images and videos directly. A video recording of the presentation is available on the DANS Youtube channel.

The report provides valuable insights from a cross-disciplinary group of leading researchers and stakeholders within brain-related disorders, with a focus on five main topics: 1) Legal, Ethical, and Societal Compliance, 2) Data Acquisition, 3) FAIR Data, 4) Models Needed for Patient Assessment, and 5) Innovation and Science Needs. The report offers a detailed roadmap to achieve the vision of improving the investigation of brain-related disorders. The results are based on careful deliberation between researchers, experts, and stakeholders following the EBRAINS CoCreate framework. EBRAINS CoCreate builds upon the method of Open Research Agenda Setting (ORAS), which recognises the benefits of engaging multiple actors in defining future research. The resulting research agendas include visions and actions that a variety of actors find important, thereby strengthening and legitimising the selection of research priorities. The EBRAINS CoCreate Improved Investigation of Brain-Related Disorders process comprised five workshop sessions arranged from February 2023 to March 2023, with the first and last workshops conducted online and the three-day workshop held in Copenhagen, Denmark. The report first takes the reader through a narrative to set the scene for the envisioned future. Thereafter, the roadmap with actions required to achieve the vision for improving the investigation of brain-related disorders is visualised and then elaborated upon with detailed descriptions of the actions. Finally, the report also highlights recommendations from the participants to demonstrate how EBRAINS can be a vital player in realising the roadmap and how the vision can be realised today., The report is co-written by each participant who attended the workshop series. Their names are listed in the report.

Introduction to FAIR principles and their application for PhDstudents.As the landscape of scientific research evolves, it becomes increasingly important to adopt practices that promote collaboration, transparency, and knowledge sharing. The FAIR principles provide a framework for enhancing, among other things, the accessibility, reusability, and long-term preservation of research data and outputs. This module aimed to introduce the FAIR principles and their relevance to Open Science, discussing the main strategies for applying them while respecting the"as open as possible, as closed as necessary" approach. Module outline: Open Science recap Data as first-class research objects FAIR principles: what they are and what they are intended for Basic components: PIDs, metadata and standards, vocabularies, repositories, licenses, etc. Open data and FAIR data Data protection Software and other research outputs Tools and resources &nbsp

Presentation as part of the Centre for Digital Scholarship - Leiden University Libraries Summer Training Week '23. Connect&Share: Licenses and Access Rights – How to Set the Appropriate Conditions for your Dataset When depositing a dataset in a data repository, you as the depositor can set the appropriate conditions for further use of your dataset. By setting access rights, you can determine who can, and who cannot, access your dataset and under which conditions. Restrictions often follow from the type of data that the dataset contains, for example in the case of personal information. A license determines what others can do with your dataset, such as reuse it for future research. There are several types of licenses that each have slightly different specifications. In this session, we will discuss how access conditions and licensing are being handled in DANS’ data repository. We also discussed projects DANS is involved in like CaRe & DaRe and ODISSEI where guidance is developed for making qualitative data and sensitive data reusable.

In RiskGONE, online tools have been developed to guide users through an ethical impact assessment (EIA), as part of a more encompassing modular risk governance framework. The EIA process is based on the CEN pre-standard on EIA (CEN CWA 17145-2:2017). In this poster, the possible added value of the EIA tools was analysed for addressing ethical impacts in decision making on whether or not, and how to share nanosafety data, based on limited open access information found on the internet, and incorporating responses to comments from ethics and data experts.

Repositories have historically focused on retrospective capture of research products, reflecting existing. research recognition systems, which do not effectively recognise non-traditional (non-text) outputs created by researchers in arts and humanities disciplines. Bulley and Sahin (2021) define practice research as a “term that describes all manners of research where practice is the significant method of research conveyed in a research output.” taking place across disciplines. In 2022, the UK’s Arts and Humanities Research Council, funded two projects – Practice Research Voices (PRVoices) and Sustaining Practice Research Assets for Research, Knowledge, Learning and Engagement (SPARKLE). They built on work done by the University of Westminster and software company Cayuse, open standards work carried out by this team in collaboration with Jisc and the British Library, and the recommendations of the PRAG-UK reports. This presentation will present the findings and recommendations of both projects to move the repositories landscape towards becoming a platform for ongoing engagement throughout the research lifecycle and beyond, capturing process and product, enabling digital preservation, and subsequently embedding in open standards. This would lead to a more equitable open research landscape where all research is recognized, discoverable and preserved and all researchers benefit from the interoperability benefits this brings.

Metadata play a fundamental role in making research data FAIR (findable, accessible, interoperable, reusable) by enhancing the discoverability, sharing and reuse of research data. They also increase confidence in the validity of the data by supporting research reproducibility. However, collecting metadata at microscopy facilities in a way that is sustainable and systematic has often proven challenging. The main barrier has been the inability to extract information from the various systems used by facilities (for example, for instrument booking). Many of these systems are part of the ecosystem of infrastructures provided by the universities that house facilities. In this report, five recommendations are proposed to foster best practices in metadata collection at microscopy facilities. These recommendations are based on the interviews of four university-based, microscopy research facilities. They focus on five key elements: 1. the choice of metadata schema; 2. the minimum set of metadata that every facility should at least collect; 3. the publication of metadata; 4. how facilities can collect metadata; and 5. how institutions can assist facilities in collecting metadata. This work was undertaken under Work Package 4: “Big-data electron and correlative microscopy from instrument to publication” of the Australian Characterisation Commons at Scale (ACCS) project.

As scientific laboratories continue to generate vast volumes of data, the need for proper handling and management of research data has become increasingly critical. The heterogeneous nature of research data further emphasizes the importance of adopting a comprehensive data management process across various career levels. This process begins with planning before project initiation, followed by ongoing monitoring and control throughout the project's duration, and concludes with defining the long-term fate of the data after project completion. Data management plans (DMPs) are the foundation of this approach. For this reason, funding agencies now commonly mandate the inclusion of a DMP in research proposals. In this talk, I will describe the fundamental elements of an effective DMP, while providing practical insights and tips specifically tailored to the fields of condensed-matter physics and materials science. Moreover, we will highlight how to prepare DMPs that align with the rigorous requirements set by the German Research Foundation (DFG) and ensures proper handling of research data., The presentation was presented during the FAIRmat users' meeting 2023 in Berlin, on June 7, 2023.

This poster outlines the concept and key elements of a research data management plan (DMP) and links to a selection of online resources.

The report provides the scope of the sustainability for the data management of the Marine subdomain, for the research infrastructures themselves and with respect to their contributions to ENVRI-FAIR and EOSC. Recommendations to consolidate the sustainability of the Marine subdomain contribution to EOSC beyond the ENVRI-FAIR project and the RI services are proposed.

FAIRCORE4EOSC is developing a set of nine EOSC-Core components necessary to enable a FAIR EOSC ecosystem, leveraging the solutions developed in previous projects and closely collaborating with the wider EOSC community in Horizon Europe. The poster was first presented at the EOSC National Tripartite Event in Italy on 5 June 2023. Discover the nine components:https://faircore4eosc.eu/eosc-core-components

International audience; The ANR SO-DRIIHM project (October 2020 - March 2024) has two main objectives, firstly to promote open science within the multidisciplinary DRIIHM community, and secondly to co-design an ergonomic "open science gateway" platform. This presentation provides an overview of the tasks carried out for each work package:- WP1: a survey on data sharing practices, the support of OHM pilot projects (data management plans, data deposits, data paper...) and the search tool for open science resources called ORRSO. We have also contributed to the data policy roadmap for CNRS-INEE infrastructures.- WP2: identify services (search data and publications, deposit data through our platform, make FAIR data as possible, draft a data paper...), set up an IT team with additional funding and carry out IT developments, involve volunteer researchers and the data steward support team in codesigning the future platform.

This is a short introduction into reusable datain context ofthe FAIR principles from Research Data Center of the University of Mannheim. It provides definition, motivation and basic ways how to make your data reusable. There is additionally a GitHub repository for the whole course:https://github.com/UB-Mannheim/FAIR-Data-Week.

Here, the Interest Group (IG) "High-performance Computing in Earth System Sciences" within NFDI4Earth (the German National Research Data Infrastructure consortium for Earth System Sciences) presents its work report for 2023, as also shown on the NFDI4Earth plenary 2023. The report relates to our concept paper (see related identifiers). The two authors have been presenting on behalf of the entire IG, as indicated in the contributors' metadata., Parts of this work have been funded by the German Research Foundation (NFDI4Earth, DFG project no. 460036893, https://www.nfdi4earth.de/).