Research Infrastructure Research Articles

The moderating role of the territorial research infrastructure on the geographic proximity effect in research collaborations: a regional-based view

The moderating role of the territorial research infrastructure on the geographic proximity effect in research collaborations: a regional-based view

Aerosol, Clouds and Trace Gases Research Infrastructure – ACTRIS, the European research infrastructure supporting atmospheric science

Abstract The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) officially became the 33rd European Research Infrastructure Consortium (ERIC) on April 25, 2023 with the support of 17 founding member and observer countries. As a pan-European legal organization, ACTRIS ERIC will coordinate the provision of data and data products on short-lived atmospheric constituents and clouds relevant to climate and air pollution over the next 15-20 years. ACTRIS was designed more than a decade ago, and its development was funded at national and European levels. It was included in the European Strategy Forum on Research Infrastructures (ESFRI) Roadmap in 2016 and subsequently, in the national infrastructure roadmaps of European countries. It became a landmark of the ESFRI roadmap in 2021. The purpose of this paper is to describe the mission of ACTRIS, its added value to the community of atmospheric scientists, providing services to academia as well as the public and private sectors, and to summarize its main achievements. The present publication serves as a reference document for ACTRIS, its users and the scientific community as a whole. It provides the reader with relevant information and an overview on ACTRIS governance and services, as well as a summary of the main scientific achievements of the last 20 years. The paper concludes with an outlook on the upcoming challenges for ACTRIS and the strategy for its future evolution.

IRIS-A New Distributed Research Infrastructure on Applied Superconductivity

IRIS-A New Distributed Research Infrastructure on Applied Superconductivity

Uniting FAIR data through interlinked, machine-actionable infrastructures

A new community of research infrastructures has joined forces to provide scientists with seamless access to the plethora of data, services and tools in biodiversity research. New levels of technological innovation and interoperability between infrastructures foster unprecedented access to biodiversity data across all data domains and the entire research lifecycle, thus advancing open science practices and strengthening Europe's position in the global biodiversity research landscape. This policy brief highlights the potential benefits derived from enhanced connectivity and interoperability among various types of biodiversity data, fostering innovation and advancements in biodiversity science, monitoring, conservation, and policy development.

Using Principal Component Analysis and Logistics Regression to Model Major Types of Cancer among Youth

Cancer poses a significant health challenge among young Nigerians due to high incidence rates and limited research on risk factors and outcomes. This study examines the utility of logistic regression and principal component analysis (PCA) in understanding cancer patterns, identifying risk factors, and predicting outcomes among Nigerian youth. Logistic regression assesses various factors such as genetics, environment, and lifestyle to predict cancer occurrence, enabling early detection and tailored interventions. PCA aids in uncovering complex data patterns by reducing dimensionality while preserving data variability. Nigeria experiences over 100,000 new cancer cases annually and a rising burden, effective statistical modelling is vital for guiding prevention and intervention strategies. The study compares different cancer types, develops risk assessment models, and forecasts cancer probabilities using logistic regression and PCA. These methodologies hold promise in enhancing cancer comprehension, diagnosis, and management among youth. Patient cancer data from the National Hospital in Abuja and the Aminu Kano Teaching Hospital in Kano were utilized, and selected through convenient sampling for accessibility and convenience. Direct observation served as the primary data collection method. This research underscores the importance of employing statistical modelling techniques, particularly logistic regression and PCA, to address the multifaceted challenges of cancer among youth. Leveraging analytical frameworks can advance early detection initiatives, tailored prevention strategies, and timely interventions, aligned with the region's unique socio-economic and cultural dynamics. Recommendations include prioritizing model validation, fostering collaborative efforts, increasing investment in cancer research infrastructure, and leveraging statistical modelling techniques to enhance cancer epidemiology understanding and healthcare outcomes among youth.

Fidelity in Academic Global Surgery and Research: Incorporating Trustworthiness in the Development of Research Partnerships, Infrastructure, and Policy.

Academic global surgery consists of collaborative partnerships that address surgical inequities through research, training, education, advocacy, and diplomacy. It has been characterized by increased scholastic production through global surgery publications, dedicated global surgery sessions within scientific conferences, global surgery-specific research grants, database development to support global surgery research, global surgery research fellowships, and global surgery-based academic promotion paradigms. The increased emphasis on global surgery research has been accompanied by multiple ethical challenges. This article reviews critical ethical dilemmas presented by global surgery research efforts and proposes interventions on the partnership, infrastructural, and policy levels to enhance fidelity within research partnerships.

A New Generation of Collaborative Immersive Analytics on the Web: Open-Source Services to Capture, Process and Inspect Users’ Sessions in 3D Environments

Recording large amounts of users’ sessions performed through 3D applications may provide crucial insights into interaction patterns. Such data can be captured from interactive experiences in public exhibits, remote motion tracking equipment, immersive XR devices, lab installations or online web applications. Immersive analytics (IA) deals with the benefits and challenges of using immersive environments for data analysis and related design solutions to improve the quality and efficiency of the analysis process. Today, web technologies allow us to craft complex applications accessible through common browsers, and APIs like WebXR allow us to interact with and explore virtual 3D environments using immersive devices. These technologies can be used to access rich, immersive spaces but present new challenges related to performance, network bottlenecks and interface design. WebXR IA tools are still quite new in the literature: they present several challenges and leave quite unexplored the possibility of synchronous collaborative inspection. The opportunity to share the virtual space with remote analysts in fact improves sense-making tasks and offers new ways to discuss interaction patterns together, while inspecting captured records or data aggregates. Furthermore, with proper collaborative approaches, analysts are able to share machine learning (ML) pipelines and constructively discuss the outcomes and insights through tailored data visualization, directly inside immersive 3D spaces, using a web browser. Under the H2IOSC project, we present the first results of an open-source pipeline involving tools and services aimed at capturing, processing and inspecting interactive sessions collaboratively in WebXR with other analysts. The modular pipeline can be easily deployed in research infrastructures (RIs), remote dedicated hubs or local scenarios. The developed WebXR immersive analytics tool specifically offers advanced features for volumetric data inspection, query, annotation and discovery, alongside spatial interfaces. We assess the pipeline through users’ sessions captured during two remote public exhibits, by a WebXR application presenting generative AI content to visitors. We deployed the pipeline to assess the different services and to better understand how people interact with generative AI environments. The obtained results can be easily adopted for a multitude of case studies, interactive applications, remote equipment or online applications, to support or accelerate the detection of interaction patterns among remote analysts collaborating in the same 3D space.

SEEIIST – a new research facility for tumor treatment and biomedical investigations with proton and ion beams

Abstract Purpose A project for the establishment of an international intergovernmental scientific organization in the region of South East Europe (South East European Institute for Sustainable Technologies - SEEIIST) is currently in progress. SEEIIST is an intergovernmental effort supported by nine countries from the region (Albania, Bosnia and Herzegovina, Bulgaria, Greece, Kosovo (This designation is without prejudice to positions on status, and is in line with UNSC 1244 and the ICJ Opinion on the Kosovo Declaration of Independence.), Montenegro, North Macedonia, Serbia and Slovenia, while Switzerland is an observer). The main goals of the project are to establish a unique research infrastructure and to form a research nucleus in the region of South-East Europe, to boost the technology transfer from European laboratories like CERN and others, to promote collaboration between science, technology, and industry, to mitigate tensions between countries in the region, and to provide platforms for the development of education. Methods The research infrastructure will include a powerful next-generation accelerator that will provide proton and ion beams for tumor treatment and biomedical research. The center will comprise of three rooms for patient treatment and two large experimental halls. Results A wide pre-clinical and clinical research program in the fields of radiobiology, medical physics, medical imaging, biophysical modeling and planning of patient treatment, design and investigation of new materials, production of isotopes for diagnosis, and treatment of patients are envisaged. Conclusions This infrastructure is unique for Europe and will attract researchers from all European countries to perform their investigations.

Geodiversity of research: geographical topic focus, author location, and collaboration. A case study of SDG 2: zero hunger

AbstractThis bibliometric study examined three aspects of geodiversity of research, namely the geographical topic focus of the study, author location, and international collaboration dynamics. The publication dataset comprised 60,000 papers from the Dimensions database that have been associated with hunger research using Digital Science’s machine learning algorithm that enhances expert led search strategies. As the research was related to hunger, papers were mapped on to the Global Hunger Index country categories as convenient classification. Only 41% of hunger-related publications that focus on countries most affected by hunger feature authors affiliated to institutions in those countries. Even fewer of those publications feature locally based authors in first or last position. These numbers gradually reverse as the level of hunger declines. We analyse sample papers in an attempt to understand the reasons for these trends. These included differences in research infrastructure, sub-authorship recognition such as acknowledgements, and limitations of the relationship between country mention and real topical focus. We did not find evidence of widespread differences between senior and overall authorship and consequently urge caution before judging international collaborations as ‘helicopter’ research based only on author country affiliations and authorship position.

Early postnatal high-dose fat-soluble enteral vitamin A supplementation for moderate or severe bronchopulmonary dysplasia or death in extremely low birthweight infants (NeoVitaA): a multicentre, randomised, parallel-group, double-blind, placebo-controlled, investigator-initiated phase 3 trial.

Vitamin A plays a key role in lung development, but there is no consensus regarding the optimal vitamin A dose and administration route in extremely low birthweight (ELBW) infants. We aimed to assess whether early postnatal additional high-dose fat-soluble enteral vitamin A supplementation versus placebo would lower the rate of moderate or severe bronchopulmonary dysplasia or death in ELBW infants receiving recommended basic enteral vitamin A supplementation. This prospective, multicentre, randomised, parallel-group, double-blind, placebo-controlled, investigator-initiated phase 3 trial conducted at 29 neonatal intensive care units in Austria and Germany assessed early high-dose enteral vitamin A supplementation (5000 international units [IU]/kg per day) or placebo (peanut oil) for 28 days in ELBW infants. Eligible infants had a birthweight of more than 400 g and less than 1000 g; gestational age at birth of 32+0 weeks postmenstrual age or younger; and the need for mechanical ventilation, non-invasive respiratory support, or supplemental oxygen within the first 72 h of postnatal age after admission to the neonatal intensive care unit. Participants were randomly assigned by block randomisation with variable block sizes (two and four). All participants received basic vitamin A supplementation (1000 IU/kg per day). The composite primary endpoint was moderate or severe bronchopulmonary dysplasia or death at 36 weeks postmenstrual age, analysed in the intention-to-treat population. This trial was registered with EudraCT, 2013-001998-24. Between March 2, 2015, and Feb 27, 2022, 3066 infants were screened for eligibility at the participating centres. 915 infants were included and randomly assigned to the high-dose vitamin A group (n=449) or the control group (n=466). Mean gestational age was 26·5 weeks (SD 2·0) and mean birthweight was 765 g (162). Moderate or severe bronchopulmonary dysplasia or death occurred in 171 (38%) of 449 infants in the high-dose vitamin A group versus 178 (38%) of 466 infants in the control group (adjusted odds ratio 0·99, 95% CI 0·73-1·55). The number of participants with at least one adverse event was similar between groups (256 [57%] of 449 in the high-dose vitamin A group and 281 [60%] of 466 in the control group). Serum retinol concentrations at baseline, at the end of intervention, and at 36 weeks postmenstrual age were similar in the two groups. Early postnatal high-dose fat-soluble enteral vitamin A supplementation in ELBW infants was safe, but did not change the rate of moderate or severe bronchopulmonary dysplasia or death and did not substantially increase serum retinol concentrations. Deutsche Forschungsgemeinschaft and European Clinical Research Infrastructures Network (ECRIN).

Pipeline Provenance for Analysis, Evaluation, Trust or Reproducibility

Data volumes and rates of research infrastructures will continue to increase in the upcoming years and impact how we interact with their final data products. Little of the processed data can be directly investigated and most of it will be automatically processed with as little user interaction as possible. Capturing all necessary information of such processing ensures reproducibility of the final results and generates trust in the entire process. We present Pipeline pRovenance for Analysis, Evaluation, Trust Or Reproducibility (PRAETOR), a software suite that enables automated generation, modeling, and analysis of provenance information of Python pipelines. Furthermore, the evaluation of the pipeline performance, based upon a user defined quality matrix in the provenance, enables the first step of machine learning processes, where such information can be fed into dedicated optimization procedures.

Research infrastructure for science and engineering (NSF)

Research infrastructure for science and engineering (NSF)

A new data infrastructure for family research and demographic analysis: the German Family Demography Panel Study (FReDA)

Abstract This data brief introduces the German Family Demography Panel Study (FReDA; https://www.freda-panel.de/), a longitudinal, multi-actor database for family research. Major substantive fields addressed in the questionnaire include fertility-related attitudes and behaviours, reproductive health, work-family conflict, couples’ division of labour, gender roles, intimate relationships, separation and divorce, parenting and intergenerational relations, and well-being. FReDA is based on two initially independent samples: the newly drawn FReDA-GGS sample (n_recruitment = 37,777 respondents, aged 18–49 years), constituting the German contribution to the Generations and Gender Surveys (GGS-II), and the FReDA-pairfam sample (n = 6,216 respondents who originally participated in the German Family Panel [pairfam]). Both samples are fully integrated, using one survey instrument consisting of the harmonized GGS-II and pairfam questionnaires. Mainly web-based interviews, complemented by paper-based interviews, are conducted biannually, with one wave being split across two subwaves. We provide a short description of FReDA’s forerunners—the GGS and pairfam—and give an overview of FReDA’s design and content, its baseline wave (collected in 2021) and data releases, as well as a brief outlook on FReDA’s road ahead.

Assessing Quality Variations in Early Career Researchers’ Data Management Plans

This paper aims to better understand early career researchers’ (ECRs’) research data management (RDM) competencies by assessing the contents and quality of  data management plans (DMPs) developed during a multi-stakeholder RDM course. We also aim to identify differences between DMPs in relation to several background variables (e.g., discipline, course track). The Basics of Research Data Management (BRDM) course has been held in two multi-faculty, research-intensive universities in Finland since 2020. In this study, 223 ECRs’ DMPs created in the BRDM of 2020 - 2022 were assessed, using the recommendations and criteria of the Finnish DMP Evaluation Guide + General Finnish DMP Guidance (FDEG). The median quality of DMPs appeared to be satisfactory. The differences in rating according to FDEG’s three-point performance criteria were statistically insignificant between DMPs developed in separate years, course tracks or disciplines. However, using content analysis, differences were found between disciplines or course tracks regarding DMP’s key characteristics such as sharing, storing, and preserving data. DMPs that contained a data table (DtDMPs) also differed highly significantly from prose DMPs. DtDMPs better acknowledged the data handling needs of different data types and improved the overall quality of a DMP. The results illustrated that the ECRs had learned the basic RDM competencies and grasped their significance to the integrity, reliability, and reusability of data. However, more focused, further training to reach the advanced competency is needed, especially in areas of handling and sharing personal data, legal issues, long-term preserving, and funders’ data policies. Equally important to the cultural change when RDM is an organic part of the research practices is to merge research support services, processes, and infrastructure into the research projects’ processes. Additionally, incentives are needed for sharing and reusing data.

Adaptive platform trials rather than randomised controlled trials for paediatric sepsis.

Adaptive platform trials (APTs) offer a promising alternative to traditional randomised controlled trials for evaluating treatments for paediatric sepsis. Randomised controlled trials, despite being the gold standard for establishing causality between interventions and outcomes, make many assumptions about disease prevalence, severity and intervention effects, which are often incorrect. As a result, the evidence for most treatments for paediatric sepsis are based on low-quality evidence. APTs use accrued data rather than assumptions to power trial adaptations. They can assess multiple treatments simultaneously with shared research infrastructure. As such, APTs offer a more efficient, flexible and more effective way to identify optimal treatments. The proposed Paediatric Adaptive Sepsis Platform Trial, leveraging the Paediatric Research in Emergency Departments International Collaborative network's infrastructure, will evaluate resuscitation fluids, vasoactive medications, corticosteroids and antimicrobials. This trial has the potential to substantially impact clinical practice and reduce global sepsis mortality in children.

Conceptual Design of the Tail Research EXperiment in Space Plasma Environment Research Facility (SPERF-TREX)

Abstract The Space Plasma Environment Research Facility (SPERF) for ground simulation of space plasma environment is a key component of Space Environment Simulation Research Infrastructure (SESRI), a major national science and technology infrastructure for fundamental researches. It is designed to investigate outstanding issues in space plasma environment, such as energetic particles acceleration, transport, and interaction with electromagnetic waves, as well as magnetic reconnection processes, in the magnetospheric plasmas, etc. Tail-Research EXperiment (TREX) is part of the SPERF for laboratory studies of space physics relevant to magnetic reconnection, dipolarization and hydromagnetic waves excitation in the magnetotail. SPERF-TREX is designed to carry out three types of experiments: the tail plasmoid for magnetic reconnection, dipolarization front formation, and magnetohydrodynamic waves excited by high speed plasma jet. In this paper, the scientific goals and three scenarios of SPERF-TREX for typical processes in space plasmas are presented, and experimental plans for SPERF-TREX are also reviewed, together with plasma sources applied to generate the plasma with desired parameters and various magnetic configurations.

Problems and potentials of research infrastructure funding in Germany on the example of the Specialized Information Service Political Science

ZusammenfassungDie Forschungsinfrastrukturförderung in Deutschland ist, wie die Forschungsförderung insgesamt, stark auf Projekte orientiert und von Drittmitteln abhängig. Diese Konstellation birgt einerseits Potenziale, zum Beispiel für technische Innovationen zur Anpassung an den digitalen Wandel. Andererseits bringt diese Ausgangslage auch Probleme mit sich, vor allem im Hinblick auf einen nachhaltigen Betrieb der Forschungsinfrastruktureinrichtungen und die großen Herausforderungen von Open Science. Der vorliegende Beitrag beleuchtet diese Konstellation anhand des Beispiels des DFG-geförderten Fachinformationsdienstes (FID) Politikwissenschaft – Pollux und fragt danach, welche Rolle Forschende für die Weiterentwicklung der Forschungsinfrastruktur spielen können.

Organizational sustainability to support Trusted Smart Statistics: Istat’s experience

The datification processes have driven National Statistical Institutes (NSIs) to explore new data sources with the goal of enhancing the quality of statistical information. The creation of innovative statistical products, known as Trusted Smart Statistics (TSS), necessitates new production processes that integrate with traditional methods, maintaining levels of relevance, quality, and trust. To facilitate this transition in statistical production, NSIs must embark on change management initiatives involving all organizational dimensions engaged in statistical processes. In the scientific debate, sustainability has assumed a broad connotation. This paper delves into the organizational aspect, viewing sustainability as a paradigm that encompasses all organizational areas and their interactions crucial to supporting the shift to new statistical production models, without compromising traditional practices. The paper explores the path taken by Istat in this direction, the organizational solutions implemented, the benefits realized, and investments in research and innovation initiated years ago on new data sources, aligning with developments in the European statistical community. Istat has been at the forefront of big data experimentation in Europe for over a decade, implementing a modernization program and establishing research infrastructures. Istat took a significant step by founding the TSS Center to guide organizational adaptation at technological, methodological, legal, communication, and human resources levels toward the new production system.

Interventions for behavioral health comorbidities in the hospice setting: a scoping review.

Behavioral health (BH) comorbidities in hospice patients are widespread and impact important outcomes, including symptom burden, quality of life, and caregiver wellbeing. However, evidencebased BH interventions tailored for the hospice setting remain understudied. We conducted a scoping review with the objective of mapping studies of interventions for BH comorbidities in the hospice setting. We included empirical studies among hospice patients of interventions with BH outcomes. We abstracted data on study design, intervention type, and patient characteristics. Our search generated 7,672 unique results, of which 37 were ultimately included in our analysis. Studies represented 16 regions, with the United Kingdom (n=13) most represented. The most frequent intervention type was complementary and alternative interventions (n=13), followed by psychotherapeutic interventions (n=12). Most of the studies were either pilot or feasibility investigations. Fifteen studies employed a randomized controlled trial design. The most frequently utilized measurement tools for BH outcomes included the Hospital Anxiety and Depression Scale and the Edmonton Symptom Assessment Scale. Seventeen studies demonstrated statistically significant results in a BH outcome measure. BH conditions prevalent among hospice patients that were the focus of intervention efforts included depression symptoms, anxiety symptoms, and general psychological distress. No study focused on trauma-related disorders or substance use disorders. This scoping review reveals a concerning gap in research regarding evidence-based BH interventions in hospice settings, especially in the U.S. Despite extensive utilization of hospice care services and the high prevalence of BH conditions among hospice patients, randomized controlled trials focused on improving BH outcomes remain scant. The current BH practices, like the widespread use of benzodiazepines and antipsychotics, may not be rooted in robust evidence, underscoring an urgent need for investment in hospice research infrastructure and tailored clinical trials to test behavioral approaches to mitigate mental health outcomes at the end of life.

Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures

This paper presents a use-case conducted within the ENVRI FAIR project, examining challenges and opportunities in deploying FAIR-aligned (ensuring Findability, Accessibility, Interoperability and Reusability) scientific name-matching services across Environmental Research Infrastructures (RIs). Six services were tested using various name variations, revealing inconsistencies in match types, status reporting and handling of canonical forms and typos. These diversities pose challenges for RI data pipelines and interoperability. The paper underscores the importance of standardised tools, enhanced communication, training, collaboration and shared resources. Addressing these needs can facilitate more effective FAIR implementation within the ENVRI community and biodiversity research. This, in turn, will empower RIs to seamlessly integrate and leverage scientific names, unlocking the full potential of their data for research and policy implementation.