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Different disciplines have vastly different ways of organising research activities, research efforts take place at a variety of scales and use a huge range of different methodologies and workflows. These silos can slow down or hinder research on topical issues like pandemics where social science can complement biomedical approaches. The challenge is to bridge the scientific domains by trying to bring together related biomedical and social science data. The BY-COVID project explores this based on a use case between the resources of the Consortium of European Social Science Data Archive (CESSDA) and the European Clinical Research Infrastructure Network (ECRIN). The work will include mapping of the DDI-based CESSDA metadata model and the ECRIN Metadata Schema for Clinical Research Data Objects, and analysis of used vocabularies and how the terms are used in different domains. This presentation will summarise findings and discuss possible areas of convergence and how the findings could be applied in the CESSDA Data Catalogue (CDC) and the Clinical Research Metadata Repository (MDR), and fed into the wider metadata discussions and EOSC debates.

This document is the first draft of the Strategic Agenda to towards the construction of the Health Research and Innovation Cloud (HRIC). The HRIC is intended to be one of the cornerstones of European Health Data Space, specifically on its incarnation devoted to secondary use of health data, building on top of existing initiatives such as the European Open Science Cloud (EOSC) building blocks. NOTE:thisdraft has not been approved by the European Commision and reflects only the opinions of the HealthyCloud Consortium.

The digitisation of healthcare has brought new opportunities to complement and enhance the data traditionally utilized in regulatory decision-making. According to the EMA, real world evidence (RWE) has been defined as the information derived from analysis of routinely collected real world data (RWD) relating to a patient’s health status or the delivery of healthcare from a variety of sources other than traditional clinical trials. Before fostering the enormous potential presented by the use of routinely collected RWD (e.g. electronic health records, medical claims, insurance data etc.) several challenges need to be addressed: operational, technical, methodological and ELSI. Reusing RWD for research purposes in Europe and especially in a crossborder manner is hampered by the fact that health databases and registries are not easily discoverable and, even when they are, understanding what data they contain and their suitability for addressing a specific research question remains not trivial due to the lack of detailed data catalogues with adequate metadata (especially in English). The present report is entitled “D4.5 Public database inventorying the national health databases and registries and describing their access procedures for reuse for research purposes”. As the title indicates, the report delivers an inventory of national health databases and registries covering 15 European countries: Austria, Czech Republic, France, Germany, Hungary, Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland. For each country the reader can find information on the national healthcare system, a list of health databases and registries, their description (or links to websites where this description can be found) and information on data access for research purposes. Although this deliverable was initially conceived as a “public database” in the form of a website, the EOSC-Life WP4 partners agreed that this would be unnecessary as the European Health Information Portal1 is already playing this role. Instead, this report will become publicly available through Zenodo and disseminated to relevant stakeholders working on similar issues (including the actors behind the Health Information Portal) as a way to “join forces” and complement each other’s work instead of duplicating efforts. In summary, we conclude that the picture across Europe is diverse and at times patchy as the health databases and registries are subject to different governance and sustainability models but also to different local laws and access rules. Interestingly, there is still, on a European level, great debate around the terms “anonymisation”, “pseudonymisation” and “de-identification” and when data can be considered anonymised and as such exempted from the GDPR. Additionally, even when the current barriers of discoverability and accessibility (that are the main focus of this report) are lifted, there remains the major question of whether such data sources are suitable for research, as concerns around their quality, completeness and structure (or lack of) are still to be addressed.

Within the BY-COVID project(https://by-covid.org/), apilot study will be performed to evaluate a simple classification system for data sharing statements of registered clinical studies, characterising the degree of willingness for data sharing, initially and specifically within COVID-19 studies. The evaluation will be performed by 3 experts on a random sample of 200 studies with a data sharing statement in a trial registry, extracted using a search of the metadata repository (MDR, https://crmdr.org/) of ECRIN. The bilateral inter-observer variability between experts will be investigated. In case of disagreement between experts a consensus will be derived to serve as the ‘source of truth’ (so called “gold standard”) for further investigations exploring the use of semi-automatic classification algorithms. Subsequent to the data sharing statement categorisation, the intention is to contact the sponsors and / or principal investigators of those trials that appear likely to provide individual participant data (IPD) and ask whether they would be willing to share IPD in the context of the BY-COVID project.

The study described is planned as part of the Horizon 2020 funded project EOSC Future (https://eoscfuture.eu/). In Work Package 6, Task 6.3 of EOSC Future, Test Science Projects (TSP) are specified. This interview guide refers to the TSP “COVID-19 metadata findability and interoperability in EOSC” (short: META-COVID). The objective of this TSP is to develop a framework for a metadata model characterising the contextual metadata and especially the research approach followed in the domain represented by each research infrastructure (RI). Contextual metadata refers to data about the research process that generated the data, and / or objects that describe that activity and to data about the ‘inputs’ into the research process – grants, people, organisations, regulators, research infrastructures etc. In the TSP a specific focus should be given to the modelling of the artifact “research activity”. The intention is to apply an iterative process of consensus building amongst experts drawn from different disciplines in the life sciences and social sciences and humanities. As a first step semi-structured interviews with representatives of the participating RIs will be performed by the European Clinical Research Infrastructure Network (ECRIN) following this interview guide. The protocol of the study is also available in Zenodo and is to be read together with the interview guide:https://zenodo.org/record/7025319#.YwjjbHHP3ct&nbsp

The qualitative study described is planned as part of the Horizon 2020 funded project EOSC Future (https://eoscfuture.eu/). In Work Package 6, Task 6.3 of EOSC Future, Test Science Projects (TSP) are specified. Relevant to this protocol is the TSP “COVID-19 metadata findability and interoperability in EOSC” (short: META-COVID). The objective of this TSP is to develop a framework for a metadata model characterising the contextual metadata and especially the research approach followed in the domain represented by each research infrastructure (RI). The intention is to apply an iterative process of consensus building amongst experts drawn from different disciplines in the life sciences and social sciences and humanities. As a first step, semi-structured interviews of representatives of individual participating RIs will be performed by the European Clinical Research Infrastructure Network (ECRIN). The study protocol has been structured according to COREQ, the consolidated criteria for reporting qualitative research (checklist for interviews and focus groups; https://pubmed.ncbi.nlm.nih.gov/17872937/). The interview guide of the study is also available in Zenodo and is to be read together with the protocol document:https://zenodo.org/record/7025502#.YwjavHZBzcs&nbsp

The present report is focused on the technical implementation and validation of the COVID-19 clinical research repository developed within the EOSC-Life project. The first section describes the functionality of the repository, split between its two main systems - the TSD infrastructure on the one hand, operated by the University of Oslo, and the Repository Management System (RMS), developed by ECRIN, on the other hand. The RMS is designed to support and record the workflows associated with managing the repository and its interactions with providers, secondary users and requesters. Subsequently, the two systems and their interface to support the repository’s activity are described in detail, including the AAI infrastructure that will be used and shared by both the RMS and the TSD. Finally, the validation strategy that is currently applied to the RMS and to the new, repository-specific elements of the TSD is outlined.

Conducting clinical trials (CTs) in the paediatric population can be difficult due to ethical, regulatory, methodological, and commercial issues influencing many factors such as procedures, sample size, and company strategies. On one hand, the lack of evidence-based research and the unmet medical needs, and on the other hand, the low investment of pharma companies in paediatric research, are increasingly promoting the use of existing resources. Sharing CTs data offer many potential benefits without conducting new studies. Although strongly recommended, a few initiatives sharing CTs data in the paediatric field still exist. In the framework of Work Package 5 “Data coordinating center and data quality standards”, scouting of initiatives (such as platforms, projects, private and public initiatives of pharma industries or no-profit organization, consortium of Sponsors/Funders, databases of pharma industries, or no-profit organization, etc.) sharing CTs data, with a focus on paediatric data, will beperformed following a specific protocol.

This deliverable summarises the work of WP1 to deliver Findable, Accessible, Interoperable and Re-usable (FAIR) services in the context of EOSC-Life’s funding calls, using these to improve FAIR services, service uptake and to inform sustainable development and future use. We describe service delivery and development around the FAIR principles and present the funded projects which have driven our implementation of FAIR Services. We address sustainability and describe the processes used to engage the EOSC-Life funded projects, as well as future work.

This deliverable summarises the work of WP1 to deliver Findable, Accessible, Interoperable and Re-usable (FAIR) services in the context of EOSC-Life’s funding calls, using these to improve FAIR services, service uptake and to inform sustainable development and future use. We describe service delivery and development around the FAIR principles and present the funded projects which have driven our implementation of FAIR Services. We address sustainability and describe the processes used to engage the EOSC-Life funded projects, as well as future work.

The scope of the report is discussed, and clarified as an examination of data standards and the interoperability of data both within and between healthcare data (including that used for observational research) and interventional research data (largely from clinical trials). The data standards in use within healthcare data are examined from the perspectives of outcome measures, syntactic and transport standards, semantic standards and metadata standards. The same is then done for standards within interventional research. The practicalities of interoperability, in particular with respect to making healthcare data more like interventional research data, are explored – again under the headings of outcome measures, syntactic and transport standards, semantic standards and metadata standards. The major finding is of a current semantic incompatibility between healthcare and interventional research data standards – i.e. they tend to use different vocabularies and concepts. A conclusion summarises the report’s findings and discusses possible actions to improve data interoperability in the short, medium and long term.

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that purpose, a toolbox is developed, providing information to researchers who wish to share or use sensitive data. The authors developed a categorisation system designed to support consistent labelling and categorisation of the resources stored in the toolboxin terms most relevant to data sharing tasks and activities, so that they are available to users (e.g., as on screen filters) when searching the system. The poster describes the methods and main results of a pilot study set to evaluate the proposed categorisation system for the toolbox resources with respect to applicability, reliability, sustainability and consistency. The primary objective of the pilot study was to identify the main improvements that are necessary to arrive at an inter-community, well understood and commonly approved categorisation system.

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is developed, providing information to researchers who wish to share sensitive data or to use sensitive data. The toolbox enables researchers to find existing resources that are relevant for sharing sensitive data across life-science research infrastructures (F in FAIR). The toolbox is based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources dealing with sensitive data. A first version of the tagging system was provided and tested in a pilot study, where 110 resources were tagged by 12 experts from 6 research infrastructures. Based on the feedback from this study, version 2 was developed and a re-tagging of the 110 resources was performed. The feedback from this 2nd study was used to further improve the categorisation system. In this document version 3 is presented with 65 tags spread over 7 dimensions: sensitive data type, resource type, research field, data type, stage in data sharing life cycle, geographical scope and specific topics.

EOSC-Life is a 4-year project funded under the European Union’s Horizon 2020 programme. Itaims to bring together the 13 Research Infrastructures in the Health and Food domain of the ESFRI Roadmap to create an open, collaborative digital space for life sciences in the European Open Science Cloud (EOSC).In March 2020, after the COVID-19 pandemic outbreak and as a rapid response to it EOSC-Life added to its work plan two new work packages to help tackle the pandemic.In EOSC-Life WP14, the European Clinical Research Infrastructure Network (ECRIN, https://ecrin.org/) has partnered with the University of Oslo (UiO, https://www.uio.no/english/) in order to commonly design, develop, implement and operate a repository for individual participant data (IPD) from COVID-19 clinical research studies that is compliant with European regulations and in particular with the GDPR.For the storage of the IPD, the TSD infrastructure of the University of Oslo will be used, which is a multitenant remote access system with a strong set of built-in security measures. The present document highlights the Data Sharing Policy of the COVID-19 repository under development in EOSC-Life WP14.A model Data Transfer Agreement for further discussions with Data Object Providers can also be madeavailable on request (contact maria.panagiotopoulou@ecrin.org). &nbsp

This paper provides an overview of ametadata schemacovering thediscoverability, access and provenanceof data objects generated by clinical research, including individual participant data sets, to help support the 'FAIRification' of those data objects. In fact twoschemas are used - one for clinical studies, based on the data structures within ClinicalTrials.gov, and the other for related data objects, based on DataCite. Because most data objects generated by clinical research do not currently have unique titles or DOIs, the expectation is that the starting point for most searches for data objects would be the source studies, hence the requirement for the two inter-related schemas. The main paper is a description of the schemas. Appendices provide further details of categorised data items, and tabular and JSON definitions of the detailed implementation of the schemas within the ECRINMDR (metadata repository).

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is developed, providing information to researchers who wish to share sensitive data or to use sensitive data. The sensitivity of the data may arise from its personal nature but can also be caused by intellectual property considerations, biohazard concerns, or the Nagoya protocol. The toolbox will not create new content, instead, it will allow researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox is based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources, in terms most relevant to data sharing tasks and activities in the Life Sciences. A first version of the tagging system was provided (version 1), covering 8 dimensions (resource type, research field, research design, data type, stage in data sharing life cycle, geographical scope, specific topics or keywords and targeted group) and evaluated in a pilot study, generating major feedback for improvement of the categorisation system. Consequently, an updated version (version 2) of the categorisation system was provided with 55 tags spread over 6 dimensions, which is described in this report.

Sharing sensitive data is a specific challenge within EOSC-Life. This deliverable reports on the preliminary results of the design of a toolbox to provide information to researchers who wish to share and/or use sensitive data in a public cloud environment in general, and in e-infrastructures adhering to the European Open Science Cloud in particular. The sensitivity of the data may arise from its personal nature, but can also be caused by intellectual property considerations, biohazard concerns, or compliance with the Nagoya protocol. The toolbox will not be based on newly generated content, instead, it will guide researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox will provide links to recommendations, procedures, and best practices, as well as to software (tools) to support data sharing and reuse. It will be based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources. The toolbox design is steered by a large working group meeting on a monthly basis with participation of a broad range of research infrastructures (the authors of this report). The current deliverable report provides a high-level summary of the results that already have been detailed further in documents published in Zenodo over the previous year, and which are referenced in this report. Finally, the document will also provide an outlook for the next steps towards the actual implementation of the toolbox and, ultimately, its sustainability beyond the EOSC-Life project’s lifetime.

Sharing sensitive data is a specific challenge within EOSC-Life. This deliverable reports on the preliminary results of the design of a toolbox to provide information to researchers who wish to share and/or use sensitive data in a public cloud environment in general, and in e-infrastructures adhering to the European Open Science Cloud in particular. The sensitivity of the data may arise from its personal nature, but can also be caused by intellectual property considerations, biohazard concerns, or compliance with the Nagoya protocol. The toolbox will not be based on newly generated content, instead, it will guide researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox will provide links to recommendations, procedures, and best practices, as well as to software (tools) to support data sharing and reuse. It will be based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources. The toolbox design is steered by a large working group meeting on a monthly basis with participation of a broad range of research infrastructures (the authors of this report).The current deliverable report provides a high-level summary of the results that already have been detailed further in documents published in Zenodo over the previous year, and which are referenced in this report. Finally, the document will also provide an outlook for the next steps towards the actual implementation of the toolbox and, ultimately, its sustainability beyond the EOSC-Life project’s lifetime.

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is being developed, providing information to researchers who wish to share and/or use sensitive data in a cloud environment in general, and the European Open Science Cloud in particular. The sensitivity of the data may arise from its personal nature but can also be caused by intellectual property considerations, biohazard concerns, or the Nagoya protocol. The toolbox will not create new content, instead, it will allow researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox will provide links to recommendations, procedures, and best practices, as well as to software (tools) to support data sharing and reuse. It will be based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources. The current design document provides an outline for the anticipated toolbox, as well as its basic principles regarding content and sustainability.

This deliverable addresses WP1’s objectives related to publication of data and data resources in cloud repositories by making available resources in EOSC-Life’s registries; the implementation of FAIR services and standards, by development of FAIR registries in collaboration with WP6; and evolution of repository infrastructure by making available registry entries deriving from WP3 demonstrators. Use cases for EOSC-Life registries have been defined for general and clinical research data use and the ‘EOSC-Life’ collection in FAIRsharing has been populated and released comprising more than 100 data resources and standards. A clinical MetaData Repository has also been developed to address challenges of clinical data sharing in Europe. We have engaged with EOSC, sister projects such as FAIRsFAIR and ENVRI to consider the features of registries, cross registry interoperability and use cases which link EOSC projects. We will continue to update the registries as the project progresses and as new dataset and resources are made available and will engage with pan-EOSC registry planning based on our work to date.

This deliverable addresses WP1’s objectives related to publication of data and data resources in cloud repositories by making available resources in EOSC-Life’s registries; the implementation of FAIR services and standards, by development of FAIR registries in collaboration with WP6; and evolution of repository infrastructure by making available registry entries deriving from WP3 demonstrators. Use cases for EOSC-Life registries have been defined for general and clinical research data use and the ‘EOSC-Life’ collection in FAIRsharing has been populated and released comprising more than 100 data resources and standards. A clinical MetaData Repository has also been developed to address challenges of clinical data sharing in Europe. We have engaged with EOSC, sister projects such as FAIRsFAIR and ENVRI to consider the features of registries, cross registry interoperability and use cases which link EOSC projects. We will continue to update the registries as the project progresses and as new dataset and resources are made available and will engage with pan-EOSC registry planning based on our work to date.

A metadata repository for clinical research

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is developed, providing information to researchers who wish to share sensitive data or to use sensitive data. The sensitivity of the data may arise from its personal nature but can also be caused by intellectual property considerations, biohazard concerns, or the Nagoya protocol. The toolbox will not create new content, instead, it will allow researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox will provide links to recommendations, procedures, and best practices, as well as to software (tools) to support data sharing and reuse. It will be based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources, in terms most relevant to data sharing tasks and activities and referring to 8 dimensions (resource type, research field, research design, data type, stage in data sharing life cycle, geographical scope, specific topics or keywords and targeted group). In this document the categorisation system is described and applied to examples. It is planned to evaluate the categorisation system within EOSC-Life in a larger pilot study.

The Horizon 2020 project EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that purpose, a toolbox is developed, providing information to researchers who wish to share or use sensitive data. An essential component of this toolbox will be a knowledge base of categorised (tagged) resources linked to sensitive data sharing in the research areas of EOSC-Life. The categories are designed to support consistent labelling and categorisation of the stored resources, in terms most relevant to data sharing tasks and activities, so that they are available to users (e.g., as on screen filters) when searching the system. Objective of the pilot study is to evaluate the applicability and appropriateness of the categorisation system, as well as the coverage of the different research areas involved in EOSC-Life. Six research infrastructures will participate in the pilot study. Three infrastructures (BBMRI, EATRIS, ECRIN) will each nominate two experts who will independently assess 25 self-selected resources. The same procedure will be applied by the other infrastructures (EMBRC, ERINHA and Euro-BioImaging) for 10 self-selected resources. The assessments will be documented per infrastructure and a summary statistics of agreements and disagreements between experts will be provided. The results will be used as a basis for an improvement and update of the categorisation system., Study protocol

This paper provides an overview of ametadata schemacovering thediscoverability, access and provenanceof data objects generated by clinical research, including individual participant data sets, to help support the 'FAIRification' of those data objects. In fact twoschemas are used - one for clinical studies, based on the data structures within ClinicalTrials.gov, and the other for related data objects, based on DataCite. Because most data objects generated by clinical research do not currently have unique titles or DOIs, the expectation is that the starting point for most searches for data objects would be the source studies, hence the requirement for the two inter-related schemas. The main paper is a description of the schemas. Appendices provide further details of categorised data items, and tabular and JSON definitions of the detailed implementation of the schemas within the ECRINMDR (metadata repository).

The deliverable highlights the necessity of data sharing in the context of the COVID-19 pandemic and provides a “high level” concept document for the design, development, implementation and use of a repository for Individual Participant Data (IPD) from COVID-19 clinical trials. In the following pages, the most important aspects for setting-up and operating the repository such as legal challenges, functional specifications, quality assurance, implementation plan, sustainability and governance, evaluation of routine use, outreach, partnerships and scalability are discussed in detail.&nbsp

The deliverable highlights the necessity of data sharing in the context of the COVID-19 pandemic and provides a “high level” concept document for the design, development, implementation and use of a repository for Individual Participant Data (IPD) from COVID-19 clinical trials. In the following pages, the most important aspects for setting-up and operating the repository such as legal challenges, functional specifications, quality assurance, implementation plan, sustainability and governance, evaluation of routine use, outreach, partnerships and scalability are discussed in detail.&nbsp

This paper provides an overview of a metadata schema, which is designed to support the discoverability of data objects generated by clinical research and is an extension of the DataCite schema.

This paper provides an overview of a metadata schema, which is designed to support the discoverability of data objects generated by clinical research and is an extension of the DataCite schema.

This paper provides an overview of a metadata schema, which is designed to support the discoverability of data objects generated by clinical research and is an extension of the DataCite schema.