搜索结果：EPJ research infrastructures

Major European Union-funded research infrastructure and open science projects have traditionally included dissemination work, for mostly one-way communication of the research activities. Here we present and review our radical re-envisioning of this work, by directly engaging citizen science volunteers into the research. We summarise the citizen science in the Horizon-funded projects ASTERICS (Astronomy ESFRI and Research Infrastructure Clusters) and ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI Research Infrastructures), engaging hundreds of thousands of volunteers in providing millions of data mining classifications. Not only does this have enormously more scientific and societal impact than conventional dissemination, but it facilitates the direct research involvement of what is often arguably the most neglected stakeholder group in Horizon projects, the science-inclined public. We conclude with recommendations and opportunities for deploying crowdsourced data mining in the physical sciences, noting that the primary goal is always the fundamental research question; if public engagement is the primary goal to optimise, then other, more targeted approache

Here, we demonstrate and investigate how Distributed Acoustic Sensing (DAS) can be utilized on research campuses and in large scientific infrastructures to study environmental vibrations and reduce their impact on high-precision experiments. We first discuss the potential of DAS in the context of particle accelerators, gravitational wave detection experiments and research campuses. Next, we present the results of our seismic measurement campaign conducted with our proto-network, which involved the probing of over 12 km of fiber, in May 2021. This campaign was conducted by the Hamburg WAVE initiative in Science City Hamburg Bahrenfeld and included DESY, the European XFEL, PETRA III and the University of Hamburg. Our proto-network confirms the ability to observe natural, anthropogenic, and infrastructural vibrations and how and where these couple into different parts of the heterogeneously set up fiber network. We also present results on a study of noise and motion coupling aspects of DAS probing double-redundant fiber loops in a unique environment, the European XFEL. Our results show that DAS greatly benefits research campuses and large scientific infrastructures and they highlight

The carbon footprint of astronomical research is an increasingly topical issue with first estimates of research institute and national community footprints having recently been published. As these assessments have typically excluded the contribution of astronomical research infrastructures, we complement these studies by providing an estimate of the contribution of astronomical space missions and ground-based observatories using greenhouse gas emission factors that relates cost and payload mass to carbon footprint. We find that worldwide active astronomical research infrastructures currently have a carbon footprint of 20.3$\pm$3.3 MtCO$_2$ equivalent (CO$_2$e) and an annual emission of 1,169$\pm$249 ktCO$_2$e yr$^{-1}$ corresponding to a footprint of 36.6$\pm$14.0 tCO$_2$e per year per astronomer. Compared with contributions from other aspects of astronomy research activity, our results suggest that research infrastructures make the single largest contribution to the carbon footprint of an astronomer. We discuss the limitations and uncertainties of our method and explore measures that can bring greenhouse gas emissions from astronomical research infrastructures towards a sustainabl

This paper presents NFDIcore 2.0, an ontology compliant with the Basic Formal Ontology (BFO) designed to represent the diverse research communities of the National Research Data Infrastructure (NFDI) in Germany. NFDIcore ensures the interoperability across various research disciplines, thereby facilitating cross-domain research. Each domain's individual requirements are addressed through specific ontology modules. This paper discusses lessons learned during the ontology development and mapping process, supported by practical validation through use cases in diverse research domains. The originality of NFDIcore lies in its adherence to BFO, the use of SWRL rules for efficient knowledge discovery, and its modular, extensible design tailored to meet the needs of heterogeneous research domains.

Research infrastructures have been identified as an important source of greenhouse gas emissions of astronomical research. Based on a comprehensive inventory of 1,211 ground-based observatories and space missions, we assessed the evolution of the number of astronomical facilities and their carbon footprint from 1945 to 2022. We found that space missions dominate greenhouse gas emissions in astronomy, showing an important peak at the end of the 1960ies, followed by a decrease that has turned again into a rise over the last decade. Extrapolating past trends, we predict that greenhouse gas emissions from astronomical facilities will experience no strong decline in the future, and may even rise substantially, unless research practices are changed. We demonstrate that a continuing growth in the number of operating astronomical facilities is not environmentally sustainable. These findings should motivate the astronomical community to reflect about the necessary evolutions that would put astronomical research on a sustainable path.

Human activities degrade the Earth environment at an unprecedented scale and pace, threatening Earth-system stability, resilience and life-support functions. We can of course deny the facts, get angry about them, or try to bargain. Or we may overcome these stages of grief and move towards accepting that human activities need to change, including our own ones. The purpose of this paper is to support astronomers in this transition, by providing insights into the origins of environmental impacts in astronomical research and proposing changes that would make the field sustainable. The paper focuses on the environmental impacts of research infrastructures, since these are the dominant sources of greenhouse gas emissions in astronomy, acknowledging that impact reductions in other areas, for example professional air travelling, need also to be achieved.

Software is at the core of most scientific discoveries today. Therefore, the quality of research results highly depends on the quality of the research software. Rigorous testing, as we know it from software engineering in the industry, could ensure the quality of the research software but it also requires a substantial effort that is often not rewarded in academia. Therefore, this research explores the effects of research software testing integrated into teaching on research software. In an in-vivo experiment, we integrated the engineering of a test suite for a large-scale network simulation as group projects into a course on software testing at the Blekinge Institute of Technology, Sweden, and qualitatively measured the effects of this integration on the research software. We found that the research software benefited from the integration through substantially improved documentation and fewer hardware and software dependencies. However, this integration was effortful and although the student teams developed elegant and thoughtful test suites, no code by students went directly into the research software since we were not able to make the integration back into the research software

This paper presents a scientometric analysis of research output from the University of Lagos, focusing on the two decades spanning 2004 to 2023. Using bibliometric data retrieved from the Web of Science, we examine trends in publication volume, collaboration patterns, citation impact, and the most prolific authors, departments, and research domains at the university. The study reveals a consistent increase in research productivity, with the highest publication output recorded in 2023. Health Sciences, Engineering, and Social Sciences are identified as dominant fields, reflecting the university's interdisciplinary research strengths. Collaborative efforts, both locally and internationally, show a positive correlation with higher citation impact, with the United States and the United Kingdom being the leading international collaborators. Notably, open-access publications account for a significant portion of the university's research output, enhancing visibility and citation rates. The findings offer valuable insights into the university's research performance over the past two decades, providing a foundation for strategic planning and policy formulation to foster research excellence

This paper presents multi- and interdisciplinary approaches for finding the appropriate AI technologies for research information. Professional research information management (RIM) is becoming increasingly important as an expressly data-driven tool for researchers. It is not only the basis of scientific knowledge processes, but also related to other data. A concept and a process model of the elementary phases from the start of the project to the ongoing operation of the AI methods in the RIM is presented, portraying the implementation of an AI project, meant to enable universities and research institutions to support their researchers in dealing with incorrect and incomplete research information, while it is being stored in their RIMs. Our aim is to show how research information harmonizes with the challenges of data literacy and data quality issues, related to AI, also wanting to underline that any project can be successful if the research institutions and various departments of universities, involved work together and appropriate support is offered to improve research information and data management.

Modern research heavily relies on software. A significant challenge researchers face is understanding the complex software used in specific research fields. We target two scenarios in this context, namely long onboarding times for newcomers and conference reviewers evaluating replication packages. We hypothesize that both scenarios can be significantly improved when there is a clear link between the paper's ideas and the code that implements them. As a time- and staff-saving approach, we propose an LLM-based automation tool that takes in a paper and the software implementing the paper, and generates a trace mapping between research ideas and their locations in code. Initial experiments have shown that the tool can generate quite useful mappings.

Demographic data collection is essential in education research, as demographic data allows researchers to better describe the participant population they study and to contextualize findings. However, current research practices for neurodiversity demographics often rely on prescriptive methods (e.g., requiring participants to report official diagnoses) rather than allowing participants to self-identify. This approach can: a) not allow participants to express their intersecting identities in ways that are authentic; and b) limit trustworthiness and reliability of the data and interpretation. In addition, inconsistent dissemination and representation of demographic data across studies hinder the accessibility and usability of this work. Through a literature review of neurodivergent student experiences with learning and performing STEM, we identified widespread discrepancies in how demographic information is collected and reported. This paper explores how neurodivergent identities can be more accurately and inclusively represented in education research. We present findings of a thematic analysis on the ways neurodivergent demographic data collection is done in the literature using data

The Global Research infrastructure (GRI) is made up of the repositories and organizations that provide persistent identifiers (PIDs) and metadata for many kinds of research objects and connect these objects to funders, research institutions, researchers, and one another using PIDs. The INFORMATE Project has combined three data sources to focus on understanding how the global research infrastructure might help the US National Science Foundation (NSF) and other federal agencies identify and characterize the impact of their support. In this paper we present INFORMATE observations of three data systems. The NSF Award database represents NSF funding while the NSF Public Access Repository (PAR) and CHORUS, as a proxy for the GRI, represent two different view of results of that funding. We compare the first at the level of awards and the second two at the level of published research articles. Our findings demonstrate that CHORUS datasets include significantly more NSF awards and more related papers than does PAR. Our findings also suggest that time plays a significant role in the inclusion of award metadata across the sources analyzed. Data in those sources travel very different journeys,

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of

This scientometric study analyzes Avian Influenza research from 2014 to 2023 using bibliographic data from the Web of Science database. We examined publication trends, sources, authorship, collaborative networks, document types, and geographical distribution to gain insights into the global research landscape. Results reveal a steady increase in publications, with high contributions from Chinese and American institutions. Journals such as PLoS One and the Journal of Virology published the highest number of studies, indicating their influence in this field. The most prolific institutions include the Chinese Academy of Sciences and the University of Hong Kong, while the College of Veterinary Medicine at South China Agricultural University emerged as the most productive department. China and the USA lead in publication volume, though developed nations like the United Kingdom and Germany exhibit a higher rate of international collaboration. "Articles" are the most common document type, constituting 84.6% of the total, while "Reviews" account for 7.6%. This study provides a comprehensive view of global trends in Avian Influenza research, emphasizing the need for collaborative efforts ac

In today's world, where societal challenges in the areas of digitalization, demographic change and sustainability are becoming increasingly complex, new innovation structures are needed to meet these challenges. Living Labs or also Real World Laboratories prove to be such. Through their applied methods such as co-creation, they integrate users into research, making it more user-centric. Which other research infrastructures exist and how they can be differentiated is presented in this paper on the basis of a systematic literature research. Furthermore, methods for user integration are examined and provided in the form of an overview.

This study investigates the challenges in designing research infrastructure software for automated software publication in multi-stakeholder environments, focusing specifically on the HERMES system. Through two quantitative surveys of research software engineers (RSEs) and infrastructure facility staff (IFs), it examines technical, organizational, and social requirements across these stakeholder groups. The study reveals significant differences in how RSEs and IFs prioritize various system features. While RSEs highly value compatibility with existing infrastructure, IFs prioritize user-focused aspects like system usability and documentation. The research identifies two main challenges in designing research infrastructure software: (1) the existence of multiple stakeholder groups with differing requirements, and (2) the internal heterogeneity within each stakeholder group across dimensions such as technical experience. The study also highlights that only half of RSE respondents actively practice software publication, pointing to potential cultural or technical barriers. Additionally, the research reveals discrepancies in how stakeholders view organizational aspects, with IFs consist

We estimate the carbon footprint of astronomical research infrastructures, including space telescopes and probes and ground-based observatories. Our analysis suggests annual greenhouse gas emissions of $1.2\pm0.2$ MtCO$_2$e yr$^{-1}$ due to construction and operation of the world-fleet of astronomical observatories, corresponding to a carbon footprint of 36.6$\pm$14.0 tCO$_2$e per year and average astronomer. We show that decarbonising astronomical facilities is compromised by the continuous deployment of new facilities, suggesting that a significant reduction in the deployment pace of new facilities is needed to reduce the carbon footprint of astronomy. We propose measures that would bring astronomical activities more in line with the imperative to reduce the carbon footprint of all human activities.

In 2018, the European Strategic Forum for research infrastructures (ESFRI) was tasked by the Competitiveness Council, a configuration of the Council of the EU, to develop a common approach for monitoring of Research Infrastructures' performance. To this end, ESFRI established a working group, which has proposed 21 Key Performance Indicators (KPIs) to monitor the progress of the Research Infrastructures (RIs) addressed towards their objectives. The RIs were then asked to assess their relevance for their institution. The paper aims to identify the relevance of certain indicators for particular groups of RIs by using cluster and discriminant analysis. This could contribute to development of a monitoring system, tailored to particular RIs. To obtain a typology of the RIs, we first performed cluster analysis of the RIs according to their properties, which revealed clusters of RIs with similar characteristics, based on to the domain of operation, such as food, environment or engineering. Then, discriminant analysis was used to study how the relevance of the KPIs differs among the obtained clusters. This analysis revealed that the percentage of RIs correctly classified into five clusters,

Humanities have convincingly argued that they need transnational research opportunities and through the digital transformation of their disciplines also have the means to proceed with it on an up to now unknown scale. The digital transformation of research and its resources means that many of the artifacts, documents, materials, etc. that interest humanities research can now be combined in new and innovative ways. Due to the digital transformations, (big) data and information have become central to the study of culture and society. Humanities research infrastructures manage, organise and distribute this kind of information and many more data objects as they becomes relevant for social and cultural research.