The Macro-Roadmap

COVID-19 Data Platform

COVID-19 Data Platform is an infrastructure that provides access to open literature and data on both the virus and the disease. It enhances researchers in their efforts towards critical information resources. The European COVID-19 Data Platform consists of three components: the COVID-19 Data Portal, the SARS-Cov-2 Data Hubs, and the Federated EGA (European Genome Phenome Archive).

Problem addressed

Data across different data types is integrated and linked to promote FAIR and open sharing and usage for the benefit of the global scientific community. Long term infrastructure is provided for SARS-CoV-2 and COVID-19 data that will remain publicly available and re-usable. The infrastructure built can be repurposed to be used for future pandemics as well.

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Workflow Hub - COVID-19 collection of workflows

A curated portfolio of workflows has been maintained and extended, with releases made widely available through WorkflowHub.The implementation of RO-Crate support for workflow runs further enhances reusability of workflows and transparency of data derivation steps. These developments are also available on the Galaxy Europe server.

Problem addressed

Data processing tasks can be slow and produce results of poor quality due to lack of interoperability between individual applications and the loss of data provenance. Workflows and processing pipelines speed up data processing, enable transparent quality and provenance management, and ensure that methods and data are openly shared and reproducible.

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Pathogens Portal

The Pathogens Portal, launched in July 2023, is an invaluable resource for researchers, clinicians, and policymakers who need access to the latest and most comprehensive datasets on pathogens.

Problem addressed

The COVID-19 pandemic has highlighted the critical importance of pathogen data sharing and the need for focused access to relevant datasets. The Pathogens Portal addresses this need by providing a centralised platform for sharing and accessing data on key pathogens, including those that can cause diseases in humans and animals, and on vectors and hosts. By bringing together data from multiple sources, and linking these data where possible, the portal enables researchers to better understand the biology and life cycles of pathogens. In addition to facilitating data sharing and research, the Pathogens Portal plays a vital role in enabling preparedness for future pandemics. By providing access to open data on emerging and endemic pathogens, the Portal helps researchers, public health officials, policymakers, clinicians and other stakeholders to access a comprehensive range of information with which to arm themselves in tackling an array of questions. The Pathogen Data Hubs form a component of the Pathogens Platform and are targetted at  public health agencies and other scientific groups responsible for generating pathogen sequencing data. Pathogen Data Hubs are in place offering a variety of configurations for upload tools and specific analysis workflows and visualisations.

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Guidelines for AI for EOSC Interoperability Framework

Guidelines for AI for EOSC Interoperability Framework.

Problem addressed

Addressing AI in the context of the EOSC Interoperability Framework.

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Cross-domain recommendations and feedback for the EOSC Interoperability Framework

FAIR-IMPACT will build on existing international frameworks and standards in scientific disciplines and on non-scientific large data sources of interest for research and will contribute to fostering the alignment between these frameworks (e.g. data sharing practices being proposed in the context of European data spaces - including open and private data-, industrial data management frameworks such as DAMA). It will strengthen collaboration with EOSC Association Task Forces supporting FAIR interoperability uptake via cross community best practice recommendations, thus feeding into the next SRIA.

Problem addressed

Fostering alignment between frameworks and strengthening collaboration with EOSC Association Task Forces supporting FAIR interoperability uptake via cross community best practice recommendations.

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Guidelines for the usage of components for technical and semantic interoperability in cross-domain use cases

FAIR-IMPACT will analyse and demonstrate semantic and technical interoperability in use cases across multiple domains. It will generate guidelines about usage of the components identified in the EOSC Interoperability Framework (EOSC IF) and that are, or will be, implemented and deployed in EOSC-related projects. This analysis will result in recommendations usable by these initiatives, and guidelines for user communities on cross-domain interoperability problems.

Problem addressed

Given the importance of research data description in the EOSC IF, FAIR-IMPACT will make a detailed analysis of how several initiatives on research data description (e.g. FAIR Digital Objects, DCAT 2.0, DDI-CDI), identified in the EOSC IF, can be applied in cross-domain use cases in order to facilitate interoperability. This analysis will result in recommendations usable by these. initiatives, and guidelines for user communities on cross-domain interoperability problems.

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OJS plugin for the EOSC Interoperability Framework on Research Product Publishing

The plugin will implement the alignment with the EOSC Interoperability Framework on Research Product Publishing and make a step towards harmonising institutional publishing platforms by solutions of known problems. It will improve the interoperability among institutional publishing platforms and the journals that use them.

Problem addressed

Increasing interoperability of Open Access Diamond publishing platforms. Open Access Diamond publishers are usually small and designed for niche research communities, so they are not made interoperable in the general case. CRAFT-OA will contribute to ensuring that publishing platforms incorporate all necessary Open Science aspects (e.g. PID, FAIR metrics & certification, AAI, etc.).

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Interoperability of Neuroscience, Cancer, Transportation and Energy Scientific Knowledge Graphs (SKGs) with the OpenAIRE Graph

SciLake will identify databases, ontologies, and taxonomies relevant to the pilots' scientific domains (neuroscience, cancer, transportation and energy) and will use these to create or extend domain-specific Scientific Knowledge Graphs (SKGs) that are interoperable with the OpenAIRE Graph. To this end, the project will identify associations between domain-specific ontologies and the main ontologies in the scholarly domains already well-represented in EOSC.

Problem addressed

Improvement in the accessibility of domain-specific knowledge. Improvement in the interoperability of domain-specific Scientific Knowledge Graphs (SKGs) with the OpenAIRE Graph. Assistance in the creation of customisable added-value services for various research communities.

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Scientific Lake as a Service

SciLake is building a data storage and analytics service to accommodate, manage, and expose heterogeneous scholarly content through domain-agnostic or domain-specific “Scientific Knowledge Graphs” together with relevant unstructured data (e.g., scientific texts). This is expected to facilitate the creation of customisable added-value services for various research communities. SciLake is building upon the OpenAIRE Graph and existing domain-specific knowledge graphs (e.g. the EBRAINS Knowledge Graph).

Problem addressed

“Scientific Lake as a Service” provides researchers with tools to create their own knowledge graphs and to integrate them with domain-agnostic science graphs to facilitate knowledge discovery and access. Because structured data is easier to retrieve, SciLake also includes tools for domain-specific experts to create structured knowledge graphs from unstructured information. As an example, the service will include text mining components that will allow users to extract information from texts and incorporate it into Scientific Knowledge Graphs. As a result, even researchers without data mining expertise will be able to access the data. The tools will also attempt to handle content in other languages besides English.

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Implementing metrics for automated FAIR digital objects assessment in a disciplinary context for F-UJI tool

FAIR-IMPACT will extend and adapt the FAIRsFAIR data object assessment metrics and F-UJI tool to be more disciplinary-context aware and to include more discipline-specific tests (social domain). F-UJI and the FAIR-Aware tool will be further developed to improve the user interface, efficiency and to identify and mitigate bias. Discipline-aware metrics and tests will be developed with use case partners, domain data repositories, research infrastructures and e-infrastructures. A reference collection of test datasets is provided for verification and benchmarking of FAIR assessment tools’ results. Pilots will test FAIR assessment tools including additional disciplinary-extended tests.

Problem addressed

Disciplinary extensions into FAIR assessment tools and enabling technical and organisational integration of assessment tools within EOSC infrastructure.

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Metrics for automated FAIR software assessment in a disciplinary context

FAIR-IMPACT will build on the outputs of the RDA/ReSA/FORCE11 FAIR for Research Software WG and existing guidelines & metrics for research software to adapt and enhance the FAIR principles for research software.

Problem addressed

Transform and project the FAIR principles and metrics into practical tests, relevant for research software, to be implemented in assessment tools for infrastructures in the scholarly ecosystem and in disciplinary contexts

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• D5.2 on Zenodo
• Release notice

Final recommendations on implementing and exposing FAIR assessments for data and code

FAIR-IMPACT supports development of guidelines and mechanisms improving connections between repository registries and discovery portals (including EOSC Portal), repository trustworthiness mechanisms (e.g. CoreTrustSeal) and FAIR digital object assessments.

Problem addressed

To enable seamless discovery of repositories (including their trustworthiness) and datasets and code (including their FAIRness).

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Federated Data Discovery and Access Services (DD&AS)

The DD&AS service facilitates discovery and retrieval of marine datasets from federated Blue Data Infrastructures (BDIs) using a common user interface. The BDIs are leading and authoritative marine data management infrastructures in the European marine research landscape and currently comprise: EMODnet, SeaDataNet, ICOS, SOCAT, EcoTaxa, ELIXIR-ENA, EurOBIS, and EuroArgo-Argo. Data cover physics, chemistry, biology, bathymetry, and genomics. More BDIs will be federated as part of Blue-Cloud 2026, such as SIOS, EMSO, EMODnet Physics, and MGnify. The service can be used stand-alone by external users, while retrieved data can also be pushed into the Blue-Cloud Virtual Research Environment (VRE) as input for data analysis and further research.

Problem addressed

Fragmentation of data sources in the marine research community. The DD&AS provides users a common interface (GUI and API) for discovery and retrieval of a large amount of marine data as managed by multiple Blue Data Infrastructures.

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COVID-19 Portal

COVID-19 Portal is a service where users may find related, comprehensive and scientific information through one portal. It harmonises and brings together different repositories and providers for different data types (open/public and sensitive data).

Problem addressed

Provision of comprehensive open data (on infectious agents and related diseases during outbreaks) supports evidence-based decision-making across scientific, medical, public health and policy domains and promotes reproducibility of research outcomes. Providers and repositories can be found and (if possible) accessed, while considering the challenge of dealing with sensitive data. The Portal is forming part of the pandemic preparedness toolkit to address future pathogen outbreaks.

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RO-Crate (Research Object Crate)

RO-Crate is a community effort to establish a lightweight approach to packaging research data with their metadata. Provenance standards have been matured and extended in collaboration with other initiatives. These include workflow related RO-Crate profiles, a Common Provenance Model and stronger support for RO-Crate has been added to the Galaxy data analysis platform.

Problem addressed

Data are only useful when their context is understood, this context is provided by metadata. However, metadata are not always captured and when they are they are not in a format that allows data analysis and reuse. RO-Crate is a user-friendly way to package data with the metadata, ensuring the data remains meaningful.

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Metadata Broker for Marine Science Data

The Blue-Cloud Metadata Broker is one of the technical service components of the Blue-Cloud Data Discovery & Access Service (DD&AS). It is based upon the DAB service as developed and managed by CNR-IIA. This middleware harvests metadata at collection level from each of the Blue Data Infrastructures (BDIs), using their web services. The Discovery and Access Broker (DAB) service transforms the harvested XML files from each of the BDIs into a common ISO Blue-Cloud collection profile, which is encoded using the recent ISO 19115-3:2016 XML profile, providing a common denominator of metadata fields, which is then published by the DAB service by means of a Blue-Cloud OGC CSW - ISO v. 2.0.2 service. The provided common denominator allows users to discover data sets in each BDI in a common way at collection level. This service is fully dynamic and currently runs every week to provide the latest index of the data collections. More technical background information can be found in the Blue-Cloud architecture document.

Problem addressed

Different stakeholder groups in marine science use various metadata schemes and ontologies. The Metadata Broker service supports configuring and providing a common denominator for the metadata schema at data collection level, while in  Blue-Cloud 2026 the Data Discovery & Access Service (DD&AS) will be expanded with also a Semantic Broker service, using ontologies, in order to provide common vocabulary terms in the metadata output.Also, it will be explored how the common denominator of metadata fields and their semantic support could be expanded in cooperation with the BDIs.

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• Blue-Cloud Data Discovery & Access Service
• D2.7 Blue Cloud Architecture (Release 2)
• ESSI-Lab-github

FAIRsharing BY-COVID Collection of Data Sources

A cross-disciplinary resource that maps and interlinks databases, standards and policies, FAIRsharing enables efficient onboarding of new data sources and a means to ensure these are more discoverable in the European Open Science Cloud (EOSC) ecosystem.The collection contains over 20 data sources, developed by BY-COVID members, from social science and humanities, health and clinical data, images, genomic and phenotypic data and chemical biology.

Problem addressed

Making a range of infectious disease data sources widely discoverable, accessible and interoperable is important for research and innovation, which is increasingly multidisciplinary in nature. For example, pathogen research is accelerated by the availability of data from clinical trials, biobanks, behavioural and socioeconomic studies, particularly if the data is combined with host and pathogen omics information. Many of these data types, for example clinical records or bioactivity data, may contain high resolution images, the availability of which extends the potential research questions which can be explored. Multidisciplinary data is also critical for public health decision-making, where policy questions are complex and evidence from biomolecular research, clinical studies and social sciences must be taken into account. One lesson from the COVID-19 pandemic was that data-driven decision-making needs high quality, real-time data from many research disciplines and geographic areas in an integrated format. The BY-COVID project is building on these learnings and creating solutions for COVID-19 that can be extended to other pathogens. Resources like the COVID-19 Data Portal and FAIRsharing are pivotal to meet these goals.

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Guidelines for recommended metadata standard for research software within EOSC

FAIR-IMPACT developed guidelines for the collection and curation of metadata to archive, reference, describe and cite research software by surveying the ecosystem of scholarly infrastructures and review existing guidelines in this area. In this, FAIR-IMPACT will follow recommendations from the EOSC SIRS report and actions from FAIR4RS and evaluate how standard metadata impacts software reproducibility.

Problem addressed

To evaluate how standard metadata impacts software reproducibility

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Report on FAIR semantic artefact lifecycle from engineering, to sharing and FAIR assessment

Establishing guidelines and community practices for FAIR semantic artefacts from creation, to sharing and reuse, via repositories and catalogues i.e. ontology repositories, registries, vocabulary/terminology services and metadata schemas catalogues.

Problem addressed

Need for guidelines and community practices for FAIR semantic artefacts and standardisation mechanisms across communities and stages of semantic artefact management.

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Use case driven validation of semantic artefact exploitation within data repositories

FAIR-IMPACT will will demonstrate the impact of FAIR semantic artefacts for data repositories and metadata catalogues. It will validate methodologies and guidelines with data driven scenarios from the use cases using semantic artefacts from their data repositories.

Problem addressed

Validation of methodologies and guidelines with data driven scenarios from the use cases using semantic artefacts from their data repositories

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Guidelines and methodology to create, document and share mappings and crosswalks

FAIR-IMPACT will develop a framework establishing bridges between metadata description of various research objects based on metadata schema crosswalks and ontology/vocabulary mappings. Such a framework will enable identification of a common “minimal metadata” representation, identified as a core requirement for EOSC (SRIA, EOSC IF); it will be based on existing community resources, models (e.g. SSSOM, CodeMeta, EDOAL, RO-Crate) and recommendations (SEMAF, FAIRsFAIR).

Problem addressed

Need for identification of a common “minimal metadata” representation, identified as a core requirement for EOSC and the establishment of a common conceptual model for mappings, crosswalks and guidelines to share them in a machine actionable format, also supporting their governance.

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EOSC PID Meta Resolver

The EOSC PID Meta Resolver (PIDMR) is a generalized resolver to map items into records and integrate them in a global network (e.g. Global Handle). It will also develop (1) a new user interface that supports easy integration and search, and (2) the metadata of different PID systems (i.e. the “Kernel Information Profiles”) to query metadata information of a PID without having to resolve it.

Problem addressed

The increasing use of Persistent Identifiers (PIDs) to reference all types of research results is a major step forward in meeting future requirements for the FAIRness of (research) data. However, this brings new challenges to process the PIDs, and to integrate them in research activities. The biggest difficulty is the multitude of systems used to create and maintain PIDs. The challenge is to know which system is responsible for the resolution process and which provides the PID metadata. The PIDMR will tackle this problem to simplify PID resolution through a uniform interface.

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Metadata and Ontologies for Publishing Platforms

This report describes requirements for aggregators and indexes of metadata standards and protocols that could be integrated into journal publishing services. It considers operational recommendations for journals without a dedicated publishing software.

Problem addressed

Metadata and ontologies are required by Open Access publishing platforms to enable discovering relevant articles.

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Bringing RO-Crate to Technology Readiness Level (TRL) 9

RO-Crate is a generic packaging format for datasets and their metadata description that uses standards for FAIR Linked Data (JSON-LD). EuroScienceGateway is completing its development by connecting all elements, tying up the loose ends and making it reach TRL 9.

Problem addressed

The integration of RO-Crate into Galaxy enables institutions that use Invenio RDM or address Zenodo instances to export immediately; thus, complete analysis histories, provenance information and identifiers get published following standards. Commonly, data will be stored locally in long-term archives. Galaxy will keep track of where the data is stored as well as the metadata. Both data and metadata can be accessed through Galaxy when needed, enabling the re-import of all assets necessary for validation or re-use.

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EOSC Metadata Schema and Crosswalk Registry (MSCR)

The EOSC Metadata Schema and Crosswalk Registry (MSCR) provides the steps to translate data from different repositories with non-compatible metadata schemas to a single metadata schema to enable data analysis by allowing to deposit or describe metadata schemas in different repositories and defining the crosswalks between them.

Problem addressed

The EOSC Metadata Schema and Crosswalk Registry (MSCR) allows users and communities to create, register and version schemas and crosswalks using Persistent Identifiers (PIDs). The content published can be searched, browsed and downloaded without restrictions. It also provides an API to facilitate the transformation of data from one schema to another via registered crosswalks. The EOSC MSCR will thus enable projects and individual researchers to manage their metadata schema and/or relevant metadata schema crosswalks. Schema and crosswalks are shared with the community for reuse and extension, supported by a proper versioning mechanism. The MSCR will be integrated with all relevant EOSC-Core services: AAI, monitoring and helpdesk.

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Research Analysis Identifier (RAI)

Research Analysis Identifier (RAI) of experiments will become a new Persistent Identifier (PID) that can be used in addition to existing PIDs. This identifier combines the result with the dataset and algorithm employed by a researcher to process the dataset.

Problem addressed

To identify, reproduce and acknowledge research analysis performer and data owner, especially in the context of controlled data.

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User Guidelines on EOSC PID Implementation

By integrating use cases and other stakeholders to support research communities FAIR-IMPACT establishes best practices around versioning, granularity, type registries, and PID minting practices for different types of datasets, workflows and research objects, as well as with other solutions that support reproducible research, actionable publications and FAIR. The developments will support coordination and build on existing work (e.g. the PID Graph) promoting efficient models for ingestion into the Graph. Identifying user needs and PID practices in different scientific communities is the top priority of this task.

Problem addressed

Document best practices around versioning, granularity, type registries, and Persistent Identifier (PID) minting practices for different types of datasets, workflows and research objects, as well as with other solutions that support reproducible research, actionable publications and FAIR.

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Shared Long-term Vision for PID Service Providers on PID Usage in EOSC

Establishment of the coordination mechanism for Persistent Identifier (PID) service providers, to help them align with the EOSC PID policy and the implementation of PID services in EOSC. It will cover PIDs for various entities, including research outputs, instruments, services, people, organisations and software; emerging new PIDs will be identified and analysed. It will establish a collaborative and shared high level vision for PID use within EOSC, thus supporting FAIRCORE4EOSC on managing PIDs in a sustainable way and the organisation of common issues.

Problem addressed

Align Persistent Identifier (PID) providers with EOSC PID Policy

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EOSC Research Discovery Graph Service

The RDGraph is an improvement of the OpenAIRE Graph that integrates new components like RAiD. FAIRCORE4EOSC will improve several existing features (e.g. data dumps, and APIs to support data re-use) and will add some new ones (e.g. “impact-based search”, to provide a way to search for data while taking into account usage statistics, and “natural language search”, to enable the use of human language to search for research data and community recommendation profiles that allows to create sub-profiles for different communities).

Problem addressed

The EOSC Research Discovery Graph Service (RDGraph) delivers advanced discovery tools across EOSC resources and communities and builds upon the EOSC Catalogue’s content.

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Research Activity Identifier (RAiD)

RAiD is a new Persistent Identifier (PID) developed by the Australian Research Data Commons (ARDC) to mint persistent, unique and resolvable information for research projects. RAiD enables users and services to manage information about project-related participants, services, and outcomes. RAiD also collects related identifies (of contributors, organisations, inputs, outputs, etc.), plus descriptive information about the project (title, description, subject, etc.), and stores them in an associated metadata record. It has been recently certified by ISO.

Problem addressed

RAiD connects existing persistent identifiers for researchers, institutions, outputs and tools with key project information to create a timeline of research projects.

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EOSC PID Graph

Enrichment of the DataCite PID graph to systematically integrate the connections between the nodes by harvesting from different/new sources, and incorporate them in AAI and data dump access.

Problem addressed

The nodes in the Persistent Identifier (PID) Graph are relatively well known, but the connections between them are not properly inventoried and systematically integrated.

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EOSC Data Type Registry

The EOSC Data Type Registry (DTR) allows the registration of Persistent Identifier (PID) metadata elements as data types, including provenance information and human readable description. The data types will be assigned a PID, which allows their use in PID metadata. Based on a validation schema, PID metadata records can then be validated.

Problem addressed

PID carry their own metadata to e.g. specify provenance, or to provide human readable descriptions. This metadata needs to be classified in a registry in order to enable machine readability and standardisation of PID schemes.

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EOSC Compliance Assessment Toolkit

The Compliance Assessment Toolkit (CAT) will support the EOSC PID policy by providing vocabulary services, API services and user interfaces. The CAT provides user and application interfaces to encode, record, and query compliance with the policy.

Problem addressed

There is currently no unambiguous way to assess the compliance of Persistent Identifier (PID) schemes in use. In order for EOSC to implement a consistent PID Policy, it needs to have an assessment tool in place to assess and verify compliance. This will be provided by the Compliance Assessment Toolkit (CAT).

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 EOSC Software Heritage Mirror

EOSC Software Heritage Mirror (SWHM) will enable EOSC to extend data collected through Software Heritage and its mirrors. The mirrors are copies of the Software Heritage universal source code archive, operated in agreement with, but independent from, the Software Heritage organisation. In order to prevent information loss, a mirror of Software Heritage will be established by GRNET to serve the EOSC community, and it will be updated regularly to follow the growth of the universal source code archive.

Problem addressed

The EOSC Software Heritage Mirror (SWHM) will improve software availability, prevent information loss, ensure unfettered access to software source code, and increase sharing and accessibility.

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EOSC Research Software APIs and Connectors

The EOSC Research Software APIs and Connectors (RSAC), developed in cooperation with FAIR-IMPACT, will create research software elements for archiving, referencing, describing and citing, based on the four pillars for EOSC recommended in the Scholarly Infrastructures of Research Software (SIRS) report (Archive, Reference, Describe, and Cite).

Problem addressed

The Research Software APIs and Connectors (RSAC) will ensure the long-term preservation of research software. It implements the key recommendations of the EOSC SIRS report to connect Scholarly Repositories, Publishers, and Aggregators with the Software Heritage universal source code archive, using the CodeMeta standard, and the SWHID, using tools and services for archival, reference, description, and citation of research software artefacts.

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Improvement of the Open Access Publishing Software

Improve existing Open Access publishing software for the three most widely used platforms: Open Journal Systems (OJS), Janeway, and Lodel.

Problem addressed

Open Access publishing platforms at research institutions are usually small and often focus on niche research disciplines having some areas better covered than others. Developing a community-oriented approach will lead to better results to respond to community needs and to find solutions to recognized issues.

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Service to Make Data Available for Processing

A service that allows researchers to open data for processing for others, retaining ownership, and preventing downloading or accessing of the data.

Problem addressed

Many researchers decide not to open their data due to fear of losing control and ownership of the data. The service will be an enabler of research analysis over datasets that are to be kept private and controlled.

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Workshop Report ‘What Does EOSC Bring to Research Infrastructure (RI) Users?’

This report summarizes the key findings of the workshop: “What does EOSC bring to the RI users?“. It provides key recommendations for the Research Infrastructures (RIs) from the user perspective.

Problem addressed

The report aims to visualise how RIs and end users will fully benefit from the EOSC added value and further progress towards a fully operational EOSC for thematic communities and researchers. It also addresses the role of ESFRI and other thematic Research Infrastructures (RIs) as crucial for the development of EOSC.

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Galaxy Distributed Infrastructure

Building a distributed network in the whole of Europe (12 distributed computing nodes in total), so that a computational job ( including VREs, like Jupyter notebooks) can be executed on national resource providers.

Problem addressed

Development of additional public (national) nodes that can be used by a large number of users. Connecting countries that do not have the resources to run their own Galaxy server, so that their computational jobs (including VREs like Jupyter notebooks) can be executed on national resource providers. Bring your own compute (BYOC). Develop a mechanism to plug-in own/institutional computing resources into the Galaxy European Science Gateway. Bring your own storage (BYOS). Develop a mechanism to plug-in own/institutional storage into the Galaxy European Science Gateway. Development of a scheduler that takes into account proximity to the data source, energy efficiency and environmental overhead when scheduling the job distribution over the European servers.

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cBioPortal as a Hub of Cancer Research

The data-integration platform cBioPortal is a well-established solution empowering (non-bioinformatic) researchers to query, visualize and analyze (gen)omics data – in combination with clinical and sample characteristics – in an intuitive and user-friendly manner. At the patient level, longitudinal views are available, offering additional insight into phenotypic and genotypic data over time, e.g. before, during and after cancer treatment. In EOSC4Cancer, colorectal cancer study data are made available through cBioPortal as part of different use-cases of the project. This data includes the underlying data models and codebooks used in the original studies to facilitate harmonization efforts and development of protocols, recommendations and best practices on how to make cancer research data available compatible with this platform.

Problem addressed

Standardization, harmonization, visualization and analysis of sensitive data (cancer research data). This work will contribute towards the creation of an interoperable cancer data research ecosystem where data from controlled access data sources, e.g. EGA, can connect with cBioPortal using at least one of the virtual research environments chosen by the project (Galaxy). It will also contribute towards increasing the  discoverability of data thanks to the use of individual beacon instances and the overall beacon network.

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White Paper 2022 on Cooperation of e-Infrastructures

This is a report that provides recommendations to strengthen communication between e-Infrastructure related organisations at European level, and their cooperation towards an enhanced and coordinated strategy setting. The White Paper 2022 discusses user environments and the need for an ecosystem of portals, ultimately accessible via a smart (AI-based) personalized dashboard.

Problem addressed

The current cooperation and coordination is ad-hoc and not properly framed among European e-Infrastructure initiatives and related organisations under the EOSC umbrella or other efforts.       e-IRG sees a clear need to enhance the coordination and cooperation among major European e-Infrastructure-related initiatives, which are an indispensable part of EOSC.       The recommendations will eventually benefit the end-users so that they can focus on their (cross-)disciplinary research, and not the infrastructures and tools.

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Virtual Research Environment (VRE) for marine research

The VRE is a cloud-based platform where users can seamlessly exploit computing environments, algorithms and data sources to support marine research.

Problem addressed

Providing a common environment for all researchers in marine science, the VRE enables the collaborative setup of new algorithms and the  sharing, reuse, and reproducibility of marine data.

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Roadmap to Build a Cancer Data Space

The roadmap will outline operating models, responsibilities, access mechanisms for a sustainable cancer dataspace.

Problem addressed

Creation of a sustainable cancer data space. Alignment of architectures and services created in the project with overall European cancer research landscape: EU Cancer mission, EOSC, European Health Data Space, other relevant HE cancer projects.

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Virtual Research Environments (VRE) to Facilitate the Analysis of Cancer Research Data

There will be two different virtual research environments (1 based in Galaxy and 1 based in OpenVRE) to facilitate the analysis of cancer research data. Both environments are already in production and specific instances for EOSC4Cancer will be created if necessary. Both environments will support the use of FAIR by design workflows, software and data.

Problem addressed

Standardization, harmonization and analysis of sensitive data (cancer research data).  Both environments have high Technology Readiness Levels (TRLs), Galaxy is TRL 9 while different OpenVRE instances vary from TRLs 7 to 9. The key element is the harmonization and standardization of relevant datasets before they can be individually or jointly analyzed using those environments. Both Galaxy and openVRE are open-source developments following best practices – including the fact of having source-code repositories. Thus, the project aims to have a collection of analytical workflows and other elements, e.g. cBioPortal, to facilitate the analysis of cancer-related data. Beyond having two environments, provide a collection of workflows for the analysis of cancer-related data.

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Data Discovery and Access System Platform for freshwater research

AquaINFRA is co-designing an EOSC-compliant pilot service that allows AquaINFRA users to seamlessly and easily find and access harmonised data from 1) the diverse set of Pan-European and national metadata catalogues, and 2) existing data infrastructures which host marine and freshwater data, as well as associated Earth system science, socioeconomic and biodiversity data.

Problem addressed

Data fragmentation in freshwater research

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Virtual Research Environment (VRE) for freshwater research

The VRE is a cloud-based platform where users can seamlessly combine computing environments, algorithms and data sources to support freshwater research.

Problem addressed

Providing a common environment for all researchers in freshwater science, the VRE enables the collaboration, sharing, reuse, and reproducibility of freshwater data.

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Joint ESFRI-EOSC Task Force

The new joint ESFRI-EOSC Task Force is an official instrument of collaboration. It will coordinate the activities between ESFRI and EOSC at the policy level and provide a structured interface between the two bodies.

Problem addressed

The objectives are to align the interests and maximise the impact of Member States/Associated Countries and European Commission efforts on Research Infrastructures (RIs) in EOSC. This includes the uptake of Open Science and FAIR principles by the RIs and the federation of RIs in EOSC and the use of the EOSC horizontal services.

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Open Science and Open Commons Initiatives Discovery Tool and Service

A tool to provide information about global Open Science and Open Commons Initiatives. The tool will also include information on the (new) RDA working groups. This corresponds to analysis of the initiatives, inclusion in a public graph database, which is part of the RDA maintenance facility (a connection to other graph databases being investigated). The database is also connected to the Landscape analysis service, which is provided as an optional component of Result 1 (Service Framework to facilitate international collaboration).

Problem addressed

To find information about global Open Science and Open Commons Initiatives including the RDA Working Groups and their outputs in an easy way.

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Open Science and Open Commons Initiatives Discovery Tool and Service

A tool to provide information about global Open Science and Open Commons Initiatives. The tool will also include information on the (new) RDA working groups. This corresponds to analysis of the initiatives, inclusion in a public graph database, which is part of the RDA maintenance facility (a connection to other graph databases being investigated). The database is also connected to the Landscape analysis service, which is provided as an optional component of Result 1 (Service Framework to facilitate international collaboration).

Problem addressed

To find information about global Open Science and Open Commons Initiatives including the RDA Working Groups and their outputs in an easy way.

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Open Science Monitoring Services and Tools

GraspOS will offer a series of services to facilitate monitoring of the Open Science (OS) impact and uptake from multiple perspectives (e.g., researcher-level, institutional-level). Indicatively, GraspOS will offer (among others): An Open Science (OS) Institutional Dashboard, a service that will support metrics and visualisations that can facilitate the implementation of the OS-aware Responsible Research Assessment (RRA) approaches for institutions and funders. An EOSC OS Researchers Dashboard, a service that will support metrics and visualisations for the adoption of OS practices at the level of the researcher, together with researcher-level performance indicators and other supporting information.

Problem addressed

GraspOS aims to extend existing research monitoring services according to the recommendations included in the Open Science Assessment Framework (OSAF). These services will be supported by the open and federated GraspOS infrastructure and will contribute in the creation of a research assessment  dataspace, providing the necessary tools to assess the adoption of Open Science. OpenAIRE partners, national and institutional Current Research Information Systems (CRIS), can pick and choose which tools and services they want to build a solution that fits their needs to show the level of OS adoption of their stakeholders.

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ESFRI Monitoring System (ESFRI MoS)

The ESFRI Monitoring System is a web-based system that acts as the central repository for all ESFRI Research Infrastructures (RIs), and contains a set of information for the ESFRI RIs.

Problem addressed

Monitoring the evolution of the ESFRI landscape.

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Service Framework to Facilitate International Collaboration

A set of services to support international collaboration in the area of research data sharing. Services include: i) tools to make international collaboration efficient (Facilitation of a RDA Working Group creation and operation), ii) tools to bring outputs to international discussions (Facilitation and communication services of a RDA Working Group) and iii) tools to locate global partners (Engagement activity together with landscape analysis). The service framework is designed to help streamline the processes of finding and engaging international partners in a structured way and creating additional sustainability of the results via facilitating community uptake.

Problem addressed

Research data challenges are a global issue. For organizations and initiatives, it is difficult to navigate the complexity of the research data sharing ecosystem. Tools to facilitate international collaboration are needed.

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• The service can be accessed via this application process.

Open Federated Infrastructure to Support Open Science-aware Responsible Research Assessment (RRA)

To enable responsible research assessment (RRA) and Open Science (OS) to be adopted, GraspOS will deliver an open and federated infrastructure architecture that will incorporate valuable data sources (e.g., the OpenAIRE Graph, OpenCitations) and will offer (a) unified ways to access their contents, (b) services to enrich their contents with missing metadata that can be valuable for the implementation of OS-aware RRA processes, and (c) OS monitoring services on top of them.

Problem addressed

The infrastructure architecture will pave the way for the creation of an open research assessment dataspace and will showcase the value of such a dataspace based on the activities of the project pilots.

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Open Science Assessment Framework (OSAF)

The Open Science Assessment Framework (OSAF) is being developed to facilitate translation of Responsible Research Assessment (RRA) principles into situated research evaluation protocols. The OSAF has three components: (1) a method to guide development and execution of Open Science (OS) aware responsible research assessment, (2) a (digital) assessment portfolio to facilitate collecting and sharing of a diverse range of contributions to be included in the assessment event, and (3) an assessment registry for publishing the evaluation protocol. The OSAF offers tailored solutions for Open-Science-aware responsible research assessment, scalable and flexible for different communities and institutions who want to promote the adoption of Open Science principles, or monitor their adoption. This is being developed together with the broader suite of GraspOS resources, such as data, tools and and services. This content will be made available in GraspOS’ open and federated dataspace.gr

Problem addressed

The Open Science Assessment Framework (OSAF) addresses the complexity and uncertainty associated with enacting Responsible Research Assessment (RRA) in situated contexts, such as national, epistemic, and career stage, with particular focus Open Science contributions (OSAF-Method); the challenge of collecting and sharing an expanded range of contributions to be considered in an assessment event (Assessment Portfolio); and the principle of increased transparency by publishing evaluation protocols, and in doing so, also providing a searchable database of OS aware, and contextualized, examples of RRA outcomes (Assessment Registry).

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Zotero and Zenodo Libraries Including Training Material on Open Science and FAIR Principles from All over Europe

Zotero and Zenodo libraries to share the compilation of references and training materials on Open Science and Open Data collected from different Competence Centres, User support Networks, Professional networks for lifelong learning, etc.

Problem addressed

Create awareness of the current Open Science and Open Data training resources available in Europe also to encourage their reuse.

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Network Starter Kit for professional networks: data steward

The Starter Kit provides support for the creation of new professional and sustainable communities. Professional communities play a key role in the context of Skills4EOSC Competence Centre network as they are seen as a tool for lifelong learning through peers.

Problem addressed

The starter kit addresses the challenges related to the emergence of data stewardship as a professional identity within Open Science and Open Data initiatives. It helps in defining responsibilities, roles, and skills for data stewards, facilitates the formation of data steward communities, and provides guidance on organizing and sustaining these communities. It also draws from different community organization models and references social psychology and management theory to support effective team building.

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Community-endorsed quality assurance and certification framework for professional training and qualifications

The Quality Assurance and certification Framework (QAF) for Open Science professional training and qualifications. It offers a reference framework (not a prescriptive requirement) to assure the quality of training materials and resources, based in four sections or sub-frameworks important in the context of Skills4EOSC project’s principles and philosophy: Minimum Viable Skillset, FAIR-by-design and ELSI (Ethical, Legal and Social Issues), in conjunction with a comprehensive evaluation framework and learning resources catalogues.

Problem addressed

Lack of standardized quality assurance criteria and frameworks has been a significant challenge in addressing the issues related to the creation and curation of high-quality learning/training materials on Open Science, FAIR data, and related topics.

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Catalogue of Open Science Career Profiles - Minimum Viable Skillsets

The Catalogue of Minimum Viable Skillset (MVS) Profiles is a resource that outlines essential skills and competences for roles in Open Science with the European Open Science Cloud (EOSC). It helps with skills development and curriculum design by connecting key competences to specific Open Science practices. Each MVS Profile within the catalogue is developed by drawing upon existing skills resources and competence frameworks, consolidating them into a concise and standardized format. The primary purpose of these profiles is to facilitate skills development, particularly in the context of curriculum and training course design.

Problem addressed

The Catalogue of Minimum Viable Skillset (MVS) Profiles is a significant outcome of the project to unify the training landscape, define competencies, clarify professional roles, and reduce fragmentation in training resources, in Open Science and FAIR data.

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FAIR-by-Design Methodology for Learning Materials

The methodology is based on the backward instructional process, extended with additional activities focused on the implementation of the FAIR principles. The document includes a discussion on granularity, scope, metadata schema, interoperability and publication in relevant repositories, together with a step-by-step six-stage workflow and checklist. The methodology will be used as blueprint for a train-the-trainer course aimed to present the practical FAIR-by-design instructional design

Problem addressed

Existing training material is fragmented and generally not FAIR-compliant, with no information on target group, length/duration, key messages, learning objectives, or documentation to ensure re-usability. By creating FAIR material, trainers (especially those who did not participate in the “train the trainers” sessions) will be able to use it as they see fit, adapting the material as needed by e.g. merging or restructuring. Proper documentation will allow the material to be reused in any field.

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BY-COVID Educational Toolkit

The BY-COVID Educational Toolkit provides teachers with resources to create lessons with young people (aged 14-19+) in English, French, Spanish, Czech and Dutch to discuss the ethics of data use in infectious disease research and pandemic preparedness.

Problem addressed

To mount a successful public health response to a pandemic, citizen data is required to inform decision making (for example the number of positive diagnostic texts in a given postal area). In many cases citizens are not aware this data is being used, how their privacy is being protected, and the potential risks involved. This educational toolkit is aimed at the adults of tomorrow, to inspire fact-based discussions around data sharing in public health.

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Skills4EOSC Competence Center Network

A coordinated network of competence centers for Open Science, FAIR research output management and EOSC, with the necessary resources (like e.g. Catalogue of Open Science Career Profiles - Minimum Viable Skillsets, Methodologies, Learning Materials) to (1) pool competences already in place at institutions and RI-/e-infrastructures, (2) establish a strategy for the "training of trainers", (3) act as multipliers to deliver lifelong training locally, and (4) support the local communities.

Problem addressed

Lack of expertise in Open Science (OS) and FAIR research outputs management among EOSC stakeholders. Absence of clear definition of data professional profiles and career paths for these roles. Fragmentation of training resources.

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cBioPortal as a Hub of Cancer Research

The data-integration platform cBioPortal is a well-established solution empowering (non-bioinformatic) researchers to query, visualize and analyze (gen)omics data – in combination with clinical and sample characteristics – in an intuitive and user-friendly manner. At the patient level, longitudinal views are available, offering additional insight into phenotypic and genotypic data over time, e.g. before, during and after cancer treatment. In EOSC4Cancer, colorectal cancer study data are made available through cBioPortal as part of different use-cases of the project. This data includes the underlying data models and codebooks used in the original studies to facilitate harmonization efforts and development of protocols, recommendations and best practices on how to make cancer research data available compatible with this platform.

Problem addressed

Standardization, harmonization, visualization and analysis of sensitive data (cancer research data). This work will contribute towards the creation of an interoperable cancer data research ecosystem where data from controlled access data sources, e.g. EGA, can connect with cBioPortal using at least one of the virtual research environments chosen by the project (Galaxy). It will also contribute towards increasing the  discoverability of data thanks to the use of individual beacon instances and the overall beacon network.

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Roadmap to Build a Cancer Data Space

The roadmap will outline operating models, responsibilities, access mechanisms for a sustainable cancer dataspace.

Problem addressed

Creation of a sustainable cancer data space. Alignment of architectures and services created in the project with overall European cancer research landscape: EU Cancer mission, EOSC, European Health Data Space, other relevant HE cancer projects.

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Virtual Research Environments (VRE) to Facilitate the Analysis of Cancer Research Data

There will be two different virtual research environments (1 based in Galaxy and 1 based in OpenVRE) to facilitate the analysis of cancer research data. Both environments are already in production and specific instances for EOSC4Cancer will be created if necessary. Both environments will support the use of FAIR by design workflows, software and data.

Problem addressed

Standardization, harmonization and analysis of sensitive data (cancer research data).  Both environments have high Technology Readiness Levels (TRLs), Galaxy is TRL 9 while different OpenVRE instances vary from TRLs 7 to 9. The key element is the harmonization and standardization of relevant datasets before they can be individually or jointly analyzed using those environments. Both Galaxy and openVRE are open-source developments following best practices – including the fact of having source-code repositories. Thus, the project aims to have a collection of analytical workflows and other elements, e.g. cBioPortal, to facilitate the analysis of cancer-related data. Beyond having two environments, provide a collection of workflows for the analysis of cancer-related data.

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COVID-19 Portal

COVID-19 Portal is a service where users may find related, comprehensive and scientific information through one portal. It harmonises and brings together different repositories and providers for different data types (open/public and sensitive data).

Problem addressed

Provision of comprehensive open data (on infectious agents and related diseases during outbreaks) supports evidence-based decision-making across scientific, medical, public health and policy domains and promotes reproducibility of research outcomes. Providers and repositories can be found and (if possible) accessed, while considering the challenge of dealing with sensitive data. The Portal is forming part of the pandemic preparedness toolkit to address future pathogen outbreaks.

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Framework for Pandemic Preparedness

BY-COVID demonstrates how EOSC and EOSC technologies, workflows, principles, standards etc. can be shaped and of value to respond to transnational access users and the needs of large user groups.

Problem addressed

BY-COVID addresses three overarching topics: The consolidation of rapid responses and technical developments from  the first two years of the pandemic (funded through range of H2020 projects) into sustainable services for pandemic preparedness Enable interdisciplinary  data mapping – with technologies that extend beyond pandemic preparedness. The linking of the CESSDA catalogues to the life science catalogues is the project flagship to-date Developing a unified framework for pandemic preparedness by collecting data, software and tools from disparate sources and bringing them together.

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COVID-19 Disease Map

The COVID-19 Disease Map enables the understanding of the molecular mechanism of COVID-19. Three main categories of data have been integrated i) omics, ii) drug targets and iii) imaging/3D structure data, implemented as an interactive plugin for end-users. Omics data are integrated as visual data overlays allowing to calculate diagram enrichment and visual analytics of expression profiles. Drug target data are used for identifier mappings to visualise molecules targeted by them. Imaging/3D structure data are used for side-by-side visualisations, displaying the imaging content and at the same time indicating relevant molecules in corresponding pathways. The omics category is integrated with broader computational workflows allowing the end-users to define their analytical steps before visualising data in the COVID-19 Disease Map.

Problem addressed

Understanding the molecular mechanisms of the SARS-CoV-2 virus enables research into treatments, vaccines and diagnostics, as well as improving knowledge of how the virus functions. It is difficult to understand the wealth of this public domain information due to the sheer volume of interrelated data involved, and, especially in a pandemic situation, the rapid production of additional data.. The COVID-19 Disease Map brings together information in a visual format, to enable rapid interrogation.

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BY-COVID Educational Toolkit

The BY-COVID Educational Toolkit provides teachers with resources to create lessons with young people (aged 14-19+) in English, French, Spanish, Czech and Dutch to discuss the ethics of data use in infectious disease research and pandemic preparedness.

Problem addressed

To mount a successful public health response to a pandemic, citizen data is required to inform decision making (for example the number of positive diagnostic texts in a given postal area). In many cases citizens are not aware this data is being used, how their privacy is being protected, and the potential risks involved. This educational toolkit is aimed at the adults of tomorrow, to inspire fact-based discussions around data sharing in public health.

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FAIRsharing BY-COVID Collection of Data Sources

A cross-disciplinary resource that maps and interlinks databases, standards and policies, FAIRsharing enables efficient onboarding of new data sources and a means to ensure these are more discoverable in the European Open Science Cloud (EOSC) ecosystem.The collection contains over 20 data sources, developed by BY-COVID members, from social science and humanities, health and clinical data, images, genomic and phenotypic data and chemical biology.

Problem addressed

Making a range of infectious disease data sources widely discoverable, accessible and interoperable is important for research and innovation, which is increasingly multidisciplinary in nature. For example, pathogen research is accelerated by the availability of data from clinical trials, biobanks, behavioural and socioeconomic studies, particularly if the data is combined with host and pathogen omics information. Many of these data types, for example clinical records or bioactivity data, may contain high resolution images, the availability of which extends the potential research questions which can be explored. Multidisciplinary data is also critical for public health decision-making, where policy questions are complex and evidence from biomolecular research, clinical studies and social sciences must be taken into account. One lesson from the COVID-19 pandemic was that data-driven decision-making needs high quality, real-time data from many research disciplines and geographic areas in an integrated format. The BY-COVID project is building on these learnings and creating solutions for COVID-19 that can be extended to other pathogens. Resources like the COVID-19 Data Portal and FAIRsharing are pivotal to meet these goals.

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