European Open Research Articles

Developing a Pan-European Open Science Training Landscape

Abstract In an environment designed to increasingly enable Open Science, not all researchers and research supporting units have the required competences. Moreover, there is a lack of clear data professionals’ profiles and corresponding career paths, and a high degree of fragmentation in training resources. This article presents the Horizon Europe project “Skills4EOSC” and other selected initiatives that contribute to the goals of the European Open Science Cloud, and in particular to the creation of a harmonised training landscape. The transition to Open Science implies that researchers and research-supporting experts acquire new skills, which also requires new and additional forms of training. Together, and step by step, efforts add up to a common and trusted pan-European ecosystem.

Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units

During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.

Specialized palliative care for hospitalized patients with SARS-CoV-2 infection: an analysis of the LEOSS registry

PurposeSymptom control for patients who were severely ill or dying from COVID-19 was paramount while resources were strained and infection control measures were in place. We aimed to describe the characteristics of SARS-CoV-2 infected patients who received specialized palliative care (SPC) and the type of SPC provided in a larger cohort.MethodsFrom the multi-centre cohort study Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS), data of patients hospitalized with SARS-CoV-2 infection documented between July 2020 and October 2021 were analysed.Results273/7292 patients (3.7%) received SPC. Those receiving SPC were older and suffered more often from comorbidities, but 59% presented with an estimated life expectancy > 1 year. Main symptoms were dyspnoea, delirium, and excessive tiredness. 224/273 patients (82%) died during the hospital stay compared to 789/7019 (11%) without SPC. Symptom control was provided most common (223/273; 95%), followed by family and psychological support (50% resp. 43%). Personal contact with friends or relatives before or during the dying phase was more often documented in patients receiving SPC compared to patients without SPC (52% vs. 30%).ConclusionIn 3.7% of SARS-CoV-2 infected hospitalized patients, the burden of the acute infection triggered palliative care involvement. Besides complex symptom management, SPC professionals also focused on psychosocial and family issues and aimed to enable personal contacts of dying patients with their family. The data underpin the need for further involvement of SPC in SARS-CoV-2 infected patients but also in other severe chronic infectious diseases.

Aligning Semantic Interoperability Frameworks with the FOXS Stack for FAIR Health Data.

FAIR Guiding Principles present a synergy with the use cases for digital health records, in that clinical data need to be found, accessible within a range of environments, and data must interoperate between systems and subsequently reused. The use of HL7 FHIR, openEHR, IHE XDS, and SNOMED CT (FOXS) together represents a specification to create an open digital health platform for modern health care applications. To describe where logical FOXS components align to the European Open Science Cloud Interoperability Framework (EOSC-IF) reference architecture for semantic interoperability. This should provide a means of defining if FOXS aligns to FAIR principles and to establish the data models and structures that support longitudinal care records as being fit to underpin scientific research. The EOSC-IF Semantic View is a representation of semantic interoperability where meaning is preserved between systems and users. This was analyzed and cross-referenced with FOXS architectural components, mapping concepts, and objects that describe content such as catalogues and semantic artifacts. Majority of conceptual Semantic View components were featured within the FOXS architecture. Semantic Business Objects are composed of a range of elements such as openEHR archetypes and templates, FHIR resources and profiles, SNOMED CT concepts, and XDS document identifiers. Semantic Functional Content comprises catalogues of metadata that were also supported by openEHR and FHIR tools. Despite some elements of EOSC-IF being vague (e.g., FAIR Digital Object), there was a broad conformance to the framework concepts and the components of a FOXS platform. This work supports a health-domain-specific view of semantic interoperability and how this may be achieved to support FAIR data for health research via a standardized framework.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany

IntroductionStudies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population.MethodsWe used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used.ResultsOverall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53–1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53–3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03–2.62).ConclusionWe identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

Use and effectiveness of remdesivir for the treatment of patients with covid-19 using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS): a multicentre cohort study

ObjectivesThe use of remdesivir (RDV) as the first drug approved for coronavirus disease 2019 (COVID-19) remains controversial. Based on the Lean European Open Survey on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infected patients (LEOSS), we aim to contribute timing-focused complementary real-world insights to its evaluation.MethodsSARS-CoV-2 infected patients between January 2020 and December 2021 treated with RDV were matched 1:1 to controls considering sociodemographics, comorbidities and clinical status. Multiple imputations were used to account for missing data. Effects on fatal outcome were estimated using uni- and multivariable Cox regression models.ResultsWe included 9,687 patients. For those starting RDV administration in the complicated phase, Cox regression for fatal outcome showed an adjusted hazard ratio (aHR) of 0.59 (95%CI 0.41–0.83). Positive trends could be obtained for further scenarios: an aHR of 0.51 (95%CI 0.16–1.68) when RDV was initiated in uncomplicated and of 0.76 (95% CI 0.55–1.04) in a critical phase of disease. Patients receiving RDV with concomitant steroids exhibited a further reduction in aHR in both, the complicated (aHR 0.50, 95%CI 0.29–0.88) and critical phase (aHR 0.63, 95%CI 0.39–1.02).ConclusionOur study results elucidate that RDV use, in particular when initiated in the complicated phase and accompanied by steroids is associated with improved mortality. However, given the limitations of non-randomized trials in estimating the magnitude of the benefit of an intervention, further randomized trials focusing on the timing of therapy initiation seem warranted.

THE METHODOLOGY OF USING THE EUROPEAN OPEN SCIENCE CLOUD IN THE PROCESS OF EDUCATION AND PROFESSIONAL DEVELOPMENT OF TEACHERS

The statement of basic materials. The structure of the methodology for using the European Open Science Cloud in the process of teaching and professional development of teachers consists of the following components: target (goal, target group), content, technological (methods, forms and means of training) and effective. An approximate plan of training sessions is given. The main steps of conducting the master class “Organization of training using European Open Science Cloud” are described.

A Data Space for Climate Science in the European Open Science Cloud

The increasing volume of data in many scientific fields demands a transformative approach to data management and analysis. The data space concept, i.e., a digital ecosystem promoting sustainable and FAIR data use, has emerged to address key challenges. This paper introduces the ENES Data Space, a domain-specific implementation for climate scientists within the European Open Science Cloud. This integrated environment offers datasets, tools, and services for data science applications. We present the motivations, architecture, and a scientific application example, demonstrating the data space’s capabilities.

Challenges of Promoting Open Science within the NI4OS-Europe Project in Hungary

National Initiatives for Open Science in Europe (NI4OS-Europe) is a Horizon 2020 project related to the European Open Science Cloud (EOSC). One of the project objectives is promoting EOSC and open science in 15 Central and East European EU states and EU-associated countries. This paper describes the variety of promoting activities carried out in Hungary as part of the NI4OS-Europe project by the Governmental Agency for IT Development (KIFÜ). Identifying good practices will give us the chance to find the best communication channels and methods to promote open science and to manage expectations of funders, researchers and librarians. The audience diversity of organized NI4OS events was analyzed in this study. The anonymized dataset based on registration forms was filtered by profession. Results suggest that events are generally visited by more librarians than researchers. The only exception is the third forum where the main Hungarian research fund as co-organizer might have attracted researchers’ attention. This suggests that librarians are considered to be in charge of open science issues in general. Usage data of the open science news feed were also studied. The 130 posts between May 2021 and April 2022 and 2500 visitors until the end of June 2022 give us the chance to learn about the characteristics of the most visited posts. We can conclude that the focus of communication is on open and FAIR data management, while other areas receive less attention. The results show that despite more international posts being published, the target group is more interested in local information.

License Clearance Tool: A holistic technical solution promoting open IP and open innovation practices among research communities

Open Science (OS) movement, remote collaboration among research communities and the increased quantity of new content, data and resources, have made it clear that traditional licensing schemes require new tools that would combine technical and legal features, as well as techno-licensing tools. In fact, the diversity of open licenses deprived from standardization frequently leads to situations where more than one open licenses with different or conflicting terms apply at the same time, and hence it gives rise to license compatibility concerns. This creates a legal uncertainty that may discourage authors, scientists, and researchers from releasing their work under an open license. In this paper, we identify legal and technological barriers that pose a challenge in adopting open science practices; thereafter, we present a new tool, named License Clearance Tool (LCT), which has been developed by the Athena RC (Greece) as part of the National Initiatives for Open Science in Europe – NI4OS-Europe (https://ni4os.eu/), a European project that contributes to the European Open Science Cloud (EOSC) by supporting its activities in Southeast Europe. LCT is an open-source tool, which provides a holistic approach addressing IP issues. LCT focuses on automating the clearance of Intellectual Property Rights (IPR) by ensuring the compatibility among different licenses included in the same resource and assists users on the selection of the most suitable license by providing a content summary of them with respect to permissions, prohibitions, and obligations in relation to the user needs. It is intended to support mainly researchers and non-legal experts in general to publish in FAIR/open modes.

Особливості формування інфраструктури відкритої науки в Україні

The growing complexity of scientific tasks and their resource capacity requires the integration of resources - information, computing, telecommunications, and others are necessary for performing scientific research and for the cooperation of scientists, both at the national and international levels. Now the development of an integrated science infrastructure that is interoperable with the European infrastructure using standards and software tools for information interaction is becoming relevant. The forming of national infrastructure should make use of the results of European initiatives regarding the integration of technical and informational resources and ensuring cooperation in conducting research. The combination of information and computing structures begins with the lowest links - institutional, departmental and national, which later will be integrating into common global infrastructures. The article considers approaches to creating conditions and structures based on the cloud technologies for more effective cooperation of scientific teams working on similar scientific problems. The main tasks for forming the basis of the Open science cloud in Ukraine at the national and institutional levels have been formulated on the basis of a detailed analysis of the experience of developing the European Open Science Cloud and regulatory documents relative to open science cloud in Ukraine. The implementation of these tasks, according to the authors, is significant. The main results of the development joint information environment for scientific research at the National Academy of Sciences of Ukraine as a prototype of the National Open Science Cloud integrated into the European Open Science Cloud was present.

Open Science Infrastructure as a key component of Open Science

The Open Science movement is a response to the accumulated problems in scholarly communication, like the "reproducibility crisis", "serials crisis", and "peer review crisis". The European Commission defines priorities of Open Science as Findable, Accessible, Interoperable and Reproducible (FAIR) data, infrastructure and services in the European Open Science Cloud (EOSC), Next generation metrics, altmetrics and rewards, the future of scientific communication, research integrity and reproducibility, education and skills and citizen science. Open Science Infrastructure is also one of four key components of Open Science defined by UNESCO. Mainly represented among Open Science Infrastructures are institutional and thematic repositories for publications, research data, software and code. Furthermore, the Open Science Infrastructure services range may include discovery, mining, publishing, the peer review process, archiving and preservation, social networking tools, training, high-performance computing, and tools for processing and analysis. Successful Open Science Infrastructure should be based on community values and responsive to needed changes. Preferably the Open Science Infrastructure should be distributed, enabling machine-actionable tools and services, supporting reusability and reproducibility, quality FAIR data, interoperability, sustainability, long-term preservation and funding.

Convalescent plasma treatment for SARS-CoV-2 infected high-risk patients: a matched pair analysis to the LEOSS cohort

Establishing the optimal treatment for COVID-19 patients remains challenging. Specifically, immunocompromised and pre-diseased patients are at high risk for severe disease course and face limited therapeutic options. Convalescent plasma (CP) has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients. We performed a retrospective analysis of 55 hospitalized COVID-19 patients from University Hospital Duesseldorf (UKD) at high risk for disease progression, in a substantial proportion due to immunosuppression from cancer, solid organ transplantation, autoimmune disease, dialysis. A matched-pairs analysis (1:4) was performed with 220 patients from the Lean European Open Survey on SARS-CoV-2-infected Patients (LEOSS) who were treated or not treated with CP. Both cohorts had high mortality (UKD 41.8%, LEOSS 34.1%). A matched-pairs analysis showed no significant effect on mortality. CP administration before the formation of pulmonary infiltrates showed the lowest mortality in both cohorts (10%), whereas mortality in the complicated phase was 27.8%. CP administration during the critical phase revealed the highest mortality: UKD 60.9%, LEOSS 48.3%. In our cohort of COVID-19 patients with severe comorbidities CP did not significantly reduce mortality in a retrospective matched-pairs analysis. However, our data supports the concept that a reduction in mortality is achievable by early CP administration.

Building National Open Science Cloud Initiatives (NOSCIs) in Southeast Europe: Supporting Research and Scholarly Communication

The Horizon 2020 project National Initiatives for Open Science in Europe—NI4OS Europe supports the development of the European Open Science Cloud (EOSC) by integrating 15 countries in Southeast Europe into the governance structure of this new pan-European research environment. Through a qualitative secondary analysis of the data collected during the project, the paper focuses on the main instrument developed by the project with the aim of enabling the integration of the partner countries in the EOSC—a network of national Open Science Cloud Initiatives (NOSCIs)—and explains how the concept of NOSCI and a wide range of related activities, tools, services, and resources foster research and open scholarly communication. The paper has three main sections: the first identifies challenges to scholarly communication in Southeast Europe, the second describes the methodology used to deal with these challenges revolving around the concept of NOSCI, whereas the third presents a set of indicators to track the change generated by project actions and discusses the impact of this methodology and project outputs in the area of scholarly communication.

PaNOSC – Making FAIR open data a reality for Photon and Neutron Science

PaNOSC – Making FAIR open data a reality for Photon and Neutron Science The Photon and Neutron Open Science Cloud (PaNOSC) is a European project enabling open science through the adoption of FAIR principles across photon and neutron (PaN) facilities in Europe. To this aim, PaNOSC has developed and provided common policies and software and services connected to and made accessible via the European Open Science Cloud (EOSC).

Towards Environmentally Sustainable Long-term Digital Preservation

ARCHIVER and Pre-Commercial Procurement funding has enabled small to medium enterprises (SMEs) to innovate and deliver new services for EOSC. Within the framework of the ARCHIVER pre-commercial procurement tender, between December 2020 and August 2021, three commercial consortia competed to deliver innovative, prototype solutions for long-term data preservation. Two of them were selected to continue with the pilot phase and deliver research-ready solutions for long-term data preservation of research data, therefore filling a gap in the current European Open Science panorama.
 Digital preservation relies on technological infrastructure (information and communication technology, ICT) that can have environmental impacts. While altering technology usage can reduce the impact of digital preservation practices, this alone is not a strategy for sustainable practice. Moving toward environmentally sustainable digital preservation requires critically examining the motivations and assumptions that shape current practice. The use of scalable cloud infrastructures can reduce the environmental impacts of long-term data preservation solutions.

Improving PHIRI performance and scalability: working within EGI-ACE

Abstract EGI-ACE is a 30-month H2020 project (Jan 2021 - June 2023) with a mission to empower researchers from all disciplines to collaborate in data- and compute-intensive Open Science, enabled by free-at-point-of-use services that are delivered through the European Open Science Cloud (EOSC). EGI-ACE delivers the EOSC Compute Platform (ECP), a federated system of compute and storage infrastructure extended with platform services to support diverse types of data processing and data analytics cases. The ECP currently includes High Throughput Compute (HTC) and Cloud Compute facilities, and will broaden its scope with High Performance Compute services later in 2022. The platform layer of the ECP provides assistance for single sign-on, transfer and federation of distributed data, interactive computing, management of large numbers of jobs, orchestration of compute clusters, AI and machine learning tasks. There are over 25 thematic services in EOSC that build on the ECP, and deliver scalable data analysis for different domains, from astrophysics, through life sciences, environmental sciences, to humanities. PHIRI participates in EGI-ACE as one of the ‘Early Adopters’ of the ECP. Under the EGI-ACE workplan PHIRI will explore reproducible population health workflows with the use of cloud computing, single-sign-on, Jupyter Notebooks and Binder services of the ECP. The tests will enable PHIRI to scale out existing data analysis notebooks to big capacity machines, to reproduce simulations and models across users, and to overall validate the technological and sustainability approaches of EGI-ACE. PHIRI will also advise the project on best ways to introduce secure processing capabilities within the ECP services.

FIPs and Practice

FIPs and Practice

Enhancing RDM in Galaxy by integrating RO-Crate

Enhancing RDM in Galaxy by integrating RO-Crate

Updating Linked Data practices for FAIR Digital Object principles

Updating Linked Data practices for FAIR Digital Object principles