Search

The article presents a comprehensive analysis of the transformation of the intellectual property rights protection system in the context of advancing artificial intelligence technologies, with a particular focus on the challenges faced by Ukrainian researchers and scientific institutions, as well as the potential for adapting successful EU experiences. The relevance of this research is driven by several factors. Firstly, the increase in data volumes and computing power has facilitated new approaches in science, where AI plays a crucial role in analysing and interpreting results. Secondly, traditional intellectual property protection mechanisms are proving inadequate as AI algorithms independently generate new knowledge. Thirdly, Ukraine's integration into the European research area necessitates the harmonization of intellectual property protection approaches, considering the specificities of AI usage. The current state of AI utilization in scientific research is analysed, including the automation of data collection and analysis, the acceleration of scientific discoveries, and the evolving role of researchers. Key risks to intellectual property rights protection are identified, particularly concerning authorship issues related to works created with the assistance of artificial intelligence, difficulties in tracking original sources, and the risks of unauthorized use of scientific data. Special attention is given to analysing the European regulatory experience regarding AI use, particularly the provisions of new EU legislation in the field of AI and its significance for safeguarding researchers' rights. A comprehensive approach to addressing the identified issues is proposed, incorporating both legal mechanisms (harmonization of legislation with EU norms) and technological solutions for protecting researchers' rights. Such solutions may include blockchain technologies, digital rights management systems, and plagiarism detection tools. Ensuring a balance between the principles of open science and the protection of intellectual property rights is an essential task. This can be achieved through the implementation of flexible licensing models and the use of AI technologies to monitor compliance with rights. It is recommended that the use of AI in scientific research be explicitly noted in the methodology, and that all data generated by artificial intelligence undergo thorough verification. [ABSTRACT FROM AUTHOR]

What emotions do affectively polarized individuals report, and how? While affect is a broad term, research suggests that different emotions predict distinct political behaviors. Therefore, it is vital to understand what emotions partisans report. However, as research on motivated reasoning suggests that people process information consistent with their partisan mind, I argue that they may not necessarily report the emotions they feel. Instead, they may ascribe normatively desirable emotions to their ingroup and normatively undesirable emotions to opposing outgroups. Doing so makes their ingroup distinct from and superior to outgroups. This article develops and showcases this argument. I analyze data in which affective polarization was likely high—interviews with radical‐right voters conducted before a major election—to illustrate what emotions partisans report and how. The discussion invites future research to test how affective polarization correlates with single emotions and whether partisans strengthen polarization by how they talk about emotions. [ABSTRACT FROM AUTHOR]

Psychological science has thrived thanks to new methods and innovative practices. Journals, including Behavior Research Methods (BRM), continue to support the dissemination and evaluation of research assets including data, software/hardware, statistical code, and databases of stimuli. However, such research assets rarely allow for computational reproducibility, meaning they are difficult to reuse. Therefore, in this preregistered report, we explore how BRM's authors and BRM structures shape the landscape of functional research assets. Our broad research questions concern: (1) How quickly methods and analytical techniques reported in BRM can be used and developed further by other scientists; (2) Whether functionality has improved following changes to BRM journal policy in support of computational reproducibility; (3) Whether we can disentangle such policy changes from changes in reproducibility over time. We randomly sampled equal numbers of papers (N = 204) published in BRM before and after the implementation of policy changes. Pairs of researchers recorded how long it took to ensure assets (data, software/hardware, statistical code, and materials) were fully operational. They also coded the completeness and reusability of the assets. While improvements were observed in all measures, only changes to completeness were altered significantly following the policy changes (d =.37). The effects varied between different types of research assets, with data sets from surveys/experiments showing the largest improvements in completeness and reusability. Perhaps more importantly, changes to policy do appear to have improved the life span of research products by reducing natural decline. We conclude with a discussion of how, in the future, research and policy might better support computational reproducibility within and beyond psychological science. [ABSTRACT FROM AUTHOR]

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures. [ABSTRACT FROM AUTHOR]

The article discusses the involvement of undergraduate students in "Many Labs" style studies, where multiple research groups collaborate to replicate or test psychological effects across different sites. While these studies offer benefits such as increased sample sizes and reduced researcher bias, there are shortcomings in providing training and opportunities for undergraduates. The authors suggest improvements like offering theoretical resources, clearer study protocols, and opportunities for data analysis and conference presentations to enhance the student experience in these studies. Ultimately, the article emphasizes the importance of supporting undergraduate researchers in collaborative scientific endeavors. [Extracted from the article]

The intentional and sustained actions to advance diversity, equity, and inclusion (DEI) in school psychology science and scholarship, will have reciprocal and dynamic influences on graduate preparation and practice. Herein, the School Psychology Review leadership team provides reflections on several of our intentional efforts, to date, to advocate for and advance DEI in school psychology scholarship, and the associated implications for graduate preparation and practice. Contemporary actions of the School Psychology Review leadership team have included; (a) establishing commitments to advocating for and advancing DEI as the foundation of our scholarship; (b) diversifying journal leadership and editorial board members to reflect the diverse student body school psychologists serve; (c) preparing future diverse journal leadership through mentored editorial fellowship programs, and a student editorial board with members from diverse backgrounds; (d) featuring special topics relevant to further understanding and supporting diverse and minoritized children, youth, families, and school communities; (e) providing professional-development opportunities and resources; (f) implementation of Open Science opportunities in the journal, (g) implementing triple anonymous peer review to reduce bias, and (h) implementing a journal action plan focused on advancing DEI. Collectively these efforts are aimed to influence positive change in advancing and sustaining DEI efforts in school psychology science, scholarship, graduate preparation and practice. [ABSTRACT FROM AUTHOR]

Urban ecosystems can provide diverse habitats for enhancing pollinator biodiversity. Here, we describe efforts to initiate a community wide conversation around pollinator friendly yard (lawn and garden) management practices in Appleton, Wisconsin, USA, using a series of projects. We began with wild bee census work at local environmental education centers and city parks, then expanded to community science common gardens as part of the "Bring Your Own Bees" project, and shifted gears to implement a No Mow May campaign. We outline the timeline of events that led to the creation of the Pollenablers group, which allowed us to work alongside city legislators and community leaders to bring No Mow May to Appleton. Through our experiences, we learned about the timescales and processes of small-town government structures, and the challenges of engaging in open science that garners media attention. Engaging in community conversations across scales was an essential component, including individual discussions, co-generation of research goals in alignment with community builders at Pollenablers meetings, and collaborating with political leaders to align legislative resolutions with research objectives. We hope that our insights inspire others to continue to "bee" change-makers in their local communities, and build systems of reciprocity to cultivate richer human, and more biodiverse, urban ecosystems. [ABSTRACT FROM AUTHOR]

Striving to build an exhaustive guidebook of the types and properties of human cells, the Human Cell Atlas' (HCA) success relies on the sampling of diverse populations, developmental stages, and tissue types. Its open science philosophy preconizes the rapid, seamless sharing of data – as openly as possible. In light of the scope and ambition of such an international initiative, the HCA Ethics Working Group (EWG) has been working to build a solid foundation to address the complexities of data collection and sharing as part of Atlas development. Indeed, a particular challenge of the HCA is the diversity of sampling scenarios (e.g., living participants, deceased donors, pediatric populations, culturally diverse backgrounds, tissues from various developmental stages, etc.), and associated ethical and legal norms, which vary across countries contributing to the effort. Hence, to the extent possible, the EWG set out to provide harmonised, international and interoperable policies and tools, to guide its research community. This paper provides a high-level overview of the types of challenges and approaches proposed by the EWG. The human cell atlas (HCA) is intended as an exhaustive guidebook of human cell types and their properties. Here Kirby et al. outline how the HCA Ethics Working Group is working to build a solid foundation to address the complexities of data collection and sharing. [ABSTRACT FROM AUTHOR]

The Danish Reproducibility Network (DKRN) is a grassroots initiative for establishing a peer-supportive reproducibility-focused academic network in Denmark. We modelled our approach on already existing national Reproducibility Networks. We consulted with researchers and research support professionals to identify the needs of the research community. Three themes emerged around policy implementation, training and the appropriate application of reproducible practices. The network aims to address these three themes in a strategic plan, which harnesses the benefits of grassroots initiatives. The mission of the DKRN is therefore to facilitate communication, peer-support, and the exchange of ideas through a network of topic and geographical nodes. The network is open to researchers and research support professionals from all career stages and disciplines. It aligns with broader international initiatives, and national institutions, positioning itself as a contributor to the Danish research ecosystem. [ABSTRACT FROM AUTHOR]

Although Virtual Reality (VR) holds massive potential, its applicability still faces challenges because some individuals experience cybersickness. This phenomenon includes general discomfort, disorientation, and/or nausea, and it threatens not only a pleasant user experience but also the user's safety. Thus, predicting a user's susceptibility without relying on screening questionnaires that focus on past experiences, would enable more pleasant, safer VR experiences, especially for first-time users. Hence, the current study uses the participant's controller input in a virtual Rod and Frame Test (RFT) as an effortlessly trackable performance measure. The RFT is an established method for measuring an individual's sense of verticality in visually displaced fields. It has been used in the context of simulator sickness and cybersickness. In line with the literature and the subjective vertical mismatch theory, a lower visual dependency is expected to be correlated positively with cybersickness. To evaluate the potential of the RFT as a screening method for cybersickness, a cybersickness-inducing virtual environment (the City) was deployed. In total, data from 76 participants were eligible for the statistical analysis. The study finds a positive correlation between lower visual dependency and cybersickness, but only for the group that took the RFT after experiencing the City and only for the post-RFT cybersickness ratings. As cybersickness symptoms were VR environment-specific, the predictive validity of the RFT considering the VR-specific attributes is limited. Further, other studies attributed different working mechanisms to explain the connection between visual dependence and cybersickness with conflicting evidence. Although the RFT is not applicable as a cybersickness screening method, the effect sizes suggest that the RFT could serve as an additional objective assessment of the individuals' current state during VR exposure. Future research should systematically explore interconnections between the various factors that contribute to cybersickness, pursuing the idea of open science for context sensitivity. [ABSTRACT FROM AUTHOR]

The document is a response to a commentary by Lu et al. on a study regarding the dynamics of the intertropical convergence zone during the early Heinrich Stadial 1. The authors re-evaluated age models using Bayesian methods and found a two-phase structure of hydroclimate during the HS1, with humid conditions in the early stage and drought conditions later on. They also addressed concerns about proxy and age uncertainties, as well as the interpretation of stalagmite records from East Asia. The authors disagreed with Lu et al.'s assertion that the ITCZ migrated southward during the early HS1, citing limitations in the TraCE simulation data. [Extracted from the article]

The academic publishing market is characterized by its oligopolistic market structure. Two aspects are particularly striking: Few large commercial publishers have high market shares in almost all research disciplines. This is reflected in high subscription and publication costs. At the same time, the majority of work for the journals is provided free of charge by researchers. The paradox can be explained by the tremendous importance of leading journals for researchers. Publishers turn this into market power. While key stakeholders in the market are primarily focusing on open access and open science, I argue in this article that competition plays a key role in increasing not only economic efficiency but also diversity and the participation of researchers. One exceptional option would be to shift the now-established "pay per article" system back to subscription models. [ABSTRACT FROM AUTHOR]

As part of the US Department of Energy's Exascale Computing Project (ECP), Rice University has been refining its HPCToolkit performance tools to better support measurement and analysis of applications executing on exascale supercomputers. To efficiently collect performance measurements of GPU-accelerated applications, HPCToolkit employs novel non-blocking data structures to communicate performance measurements between tool threads and application threads. To attribute performance information in detail to source lines, loop nests, and inlined call chains, HPCToolkit performs parallel analysis of large CPU and GPU binaries involved in the execution of an exascale application to rapidly recover mappings between machine instructions and source code. To analyze terabytes of performance measurements gathered during executions at exascale, HPCToolkit employs distributed-memory parallelism, multithreading, sparse data structures, and out-of-core streaming analysis algorithms. To support interactive exploration of profiles up to terabytes in size, HPCToolkit's hpcviewer graphical user interface uses out-of-core methods to visualize performance data. The result of these efforts is that HPCToolkit now supports collection, analysis, and presentation of profiles and traces of GPU-accelerated applications at exascale. These improvements have enabled HPCToolkit to efficiently measure, analyze and explore terabytes of performance data for executions using as many as 64K MPI ranks and 64K GPU tiles on ORNL's Frontier supercomputer. HPCToolkit's support for measurement and analysis of GPU-accelerated applications has been employed to study a collection of open-science applications developed as part of ECP. This paper reports on these experiences, which provided insight into opportunities for tuning applications, strengths and weaknesses of HPCToolkit itself, as well as unexpected behaviors in executions at exascale. [ABSTRACT FROM AUTHOR]

The article discusses the importance of diversity, equity, and inclusion in developmental science. It highlights the need for representative samples, diverse research participants, and inclusive scientific practices to enhance the understanding of human development. The text emphasizes the impact of sociocultural factors on developmental processes and calls for a broader perspective that considers global diversity. It also addresses challenges and opportunities in implementing open science practices to promote inclusivity and transparency in research. The article concludes by outlining priorities for achieving a diverse, equitable, and inclusive science in developmental research. [Extracted from the article]

Purpose: This study investigates the multifaceted barriers and facilitators affecting research data sharing across the research data lifecycle. It aims to broaden the understanding of data sharing beyond the publication phase, emphasizing the continuous nature of data sharing from generation to reuse. Design/methodology/approach: Employing a mixed-methods approach, the study integrates the Theory of Planned Behavior, the Technology Acceptance Model, and the Institutional Theory to hypothesize the influence of various factors on data sharing behaviors across the lifecycle. A questionnaire survey and structural equation modeling are utilized to empirically test these hypotheses. Findings: This study identifies critical factors influencing data sharing at different lifecycle stages, including perceived behavioral control, perceived effort, journal and funding agency pressures, subjective norms, perceived risks, resource availability, and perceived benefits. The findings highlight the complex interplay of these factors and their varying impacts at different stages of data sharing. Research limitations/implications: This study illuminates the dynamics of research data sharing, offering insights while recognizing its scope might not capture all disciplinary and cultural nuances. It highlights pathways for stakeholders to bolster data sharing, suggesting a collaborative push towards open science, reflecting on how strategic interventions can bridge existing gaps in practice. Practical implications: This study offers actionable recommendations for policymakers, journals, and institutions to foster a more conducive environment for data sharing, emphasizing the need for support mechanisms at various lifecycle stages. Originality/value: This study contributes to the literature by offering a comprehensive model of the research data lifecycle, providing empirical evidence on the factors influencing data sharing across this continuum. [ABSTRACT FROM AUTHOR]

The article discusses the comparison between two radiomics research quality scoring tools, METRICS and RQS, highlighting their unique features and differences. METRICS, endorsed by leading imaging societies, aims to standardize the methodological quality assessment of radiomics research, while RQS has been widely adopted in the research community despite its limitations. The article presents hypothetical scenarios to compare the two tools, emphasizing the distinct focus of each on different aspects of the radiomic pipeline. Researchers are advised to consider the unique features of each tool based on the insights provided in the analysis. [Extracted from the article]

Scholars need to be able to trust each other, because otherwise they cannot collaborate and use each other's findings. Similarly trust is essential for research to be applied for individuals, society or the natural environment. The trustworthiness is threatened when researchers engage in questionable research practices or worse. By adopting open science practices, research becomes transparent and accountable. Only then it is possible to verify whether trust in research findings is justified. The magnitude of the issue is substantial with a prevalence of four percent for both fabrication and falsification, and more than 50% for questionable research practices. This implies that researchers regularly engage in behaviors that harm the validity and trustworthiness of their work. What is good for the quality and reliability of research is not always good for a scholarly career. Navigating this dilemma depends on how virtuous the researcher at issue is, but also on the local research climate and the perverse incentives in the way the research system functions. Research institutes, funding agencies and scholarly journals can do a lot to foster research integrity, first and foremost by improving the quality of peer review and reforming researcher assessment. [ABSTRACT FROM AUTHOR]

Copyright of Methods in Ecology & Evolution is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The 2020--2022 pandemic highlighted concerns about "information disorders", pressing for approaches capable of guiding the science-society alliance toward a mutually beneficial direction. This essay advocates for and presents a framework proposing the combination of Open Science (OS) and Science Communication (SciComm) practices. OS encourages public access to scientific material, while SciComm has historically enabled public understanding of scientific knowledge. Despite their similar goals, these two communities are disconnected. We draw on the concepts of "boundary object" and "epistemic trust" to demonstrate how this framework could foster a bond between scientific expertise and public reason toward an informed and inclusive common good. The OS-SciComm framework is based on the notion that ensuring transparency in science also requires "bridging tools" that deal with the complexity of scientific lexicon and processes. It values scientific expertise, but does not undermine citizens' capabilities in information processing and their interest in accessing scientific outputs. Our proposal also acknowledges controversies involving open scientific materials during the COVID-19 pandemic and advises caution when drawing conclusions from cases that are often context-specific. The OS-SciComm framework requires innovative ideas, platforms and actions. We invite both communities to join us in this endeavor. [ABSTRACT FROM AUTHOR]

Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of results via preprints and openly sharing outputs such as data and code to make research more reproducible and extensible. Existing evidence shows that adopting Open Science practices has effects in several domains. In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122'000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% (±.7) on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% (±.8) on average. However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers. [ABSTRACT FROM AUTHOR]

Since the introduction of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles in 2016, discussions have evolved beyond the original focus on research data to include learning resources. In 2020, a set of simple rules to FAIRify learning resources was proposed, building on existing expertise within the training community. Disciplinary communities have played an important role in advancing FAIR principles for learning resources, although they have approached FAIRification activities in different ways. These communities range from volunteer-led to funded and independent organisations, however commonly include activities such as organising training and capacity building, and coordinated discussions on disciplinary-focused FAIR best practises and standards. Eight disciplinary community case studies are presented and analysed in this paper to examine the motivations, challenges and opportunities towards FAIRification of learning resources, reflecting on how community structure leads to differing responsibilities. The case studies are based on reflections formulated in 2022, the aim is to pull together the experiences of these different communities, focusing on the processes and challenges they encountered, in order to structure this knowledge across different learning platforms, draw attention to the question of sustainability for learning resources and anticipate improvements in future policies and governance. [ABSTRACT FROM AUTHOR]

Replications confront existing explanations with new evidence by retesting prior claims using new data and similar research procedures. Publishing replication studies remains uncommon in the geographic literature. Place-to-place variations make it unclear whether the results and claims of a study should be expected to replicate across locations, and a lack of experimental control makes it challenging to implement replications that can provide clear evidence about those same results and claims. The small number of studies that have attempted to replicate geographic research suggest that many studies cannot be fully replicated or are simply missing information needed to attempt a replication. Accordingly, it remains unclear how geographic researchers view replication and its role in the knowledge accumulation process. To address this question, we surveyed geographic researchers about their understanding of replicability, beliefs about what factors affect the chances of replicating a study, motivations to attempt replication studies, and experiences conducting replications. The results of our survey suggest that researchers are familiar with replication and believe that replication studies can serve a range of epistemic purposes. Nonetheless, only a small percentage of geographic researchers attempt or publish replications due to a lack of incentives. Researchers are similarly uncertain whether it is currently valuable to replicate geographic research. These findings could in part be due to differences between research traditions, and it might be fruitful to further examine how researchers working in different subfields perceive and use replication in their work. [ABSTRACT FROM AUTHOR]

Openness and transparency in the research process are a prerequisite to the production of high quality research outputs. Efforts to maximise these features have substantially accelerated in recent years, placing open and transparent research practices at the forefront of funding and related priorities, and encouraging investment in resources and infrastructure to enable such practices. Despite these efforts, there has been no systematic documentation of current practices, infrastructure, or training and resources that support open and transparent research in the UK. To address this gap, we developed and conducted the Open and Transparent Research Practices survey, a large-scale audit study completed by research-active staff in UK research institutions to better understand existing practices, needs, support, and barriers faced when implementing open and transparent research. The data presented here capture responses from over 2,500 research-active staff based at 15 institutions affiliated with the UK Reproducibility Network. The data provide a snapshot of open research practices that can be used to identify barriers, training needs, and areas that require greater investments. [ABSTRACT FROM AUTHOR]

The increasing technical complexity of all aspects involving bioimages, ranging from their acquisition to their analysis, has led to a diversification in the expertise of scientists engaged at the different stages of the discovery process. Although this diversity of profiles comes with the major challenge of establishing fruitful interdisciplinary collaboration, such collaboration also offers a superb opportunity for scientific discovery. In this Perspective, we review the different actors within the bioimaging research universe and identify the primary obstacles that hinder their interactions. We advocate that data sharing, which lies at the heart of innovation, is finally within reach after decades of being viewed as next to impossible in bioimaging. Building on recent community efforts, we propose actions to consolidate the development of a truly interdisciplinary bioimaging culture based on open data exchange and highlight the promising outlook of bioimaging as an example of multidisciplinary scientific endeavour. [ABSTRACT FROM AUTHOR]

Over the past two decades, extensive studies, particularly in cancer analysis through large datasets like The Cancer Genome Atlas (TCGA), have aimed at improving patient therapies and precision medicine. However, limited overlap and inconsistencies among gene signatures across different cohorts pose challenges. The dynamic nature of the transcriptome, encompassing diverse RNA species and functional complexities at gene and isoform levels, introduces intricacies, and current gene signatures face reproducibility issues due to the unique transcriptomic landscape of each patient. In this context, discrepancies arising from diverse sequencing technologies, data analysis algorithms, and software tools further hinder consistency. While careful experimental design, analytical strategies, and standardized protocols could enhance reproducibility, future prospects lie in multiomics data integration, machine learning techniques, open science practices, and collaborative efforts. Standardized metrics, quality control measures, and advancements in single-cell RNA-seq will contribute to unbiased gene signature identification. In this perspective article, we outline some thoughts and insights addressing challenges, standardized practices, and advanced methodologies enhancing the reliability of gene signatures in disease transcriptomic research. [ABSTRACT FROM AUTHOR]

The article emphasizes the importance of transparency in scientific research, specifically focusing on the benefits of preregistration and registered reporting to enhance credibility and reproducibility. It discusses the value of separating hypothesis-testing and hypothesis-generating analyses, as well as the role of interdisciplinary collaborations in study design. The study also addresses common misconceptions about registered reports, highlighting their applicability across various disciplines and their contribution to improving research quality and credibility, particularly in the biomedical field. [Extracted from the article]

The use of synthetic data in pharmacology research has gained significant attention due to its potential to address privacy concerns and promote open science. In this study, we implemented and compared three synthetic data generation methods, CT‐GAN, TVAE, and a simplified implementation of Avatar, for a previously published pharmacogenetic dataset of 253 patients with one measurement per patient (non‐longitudinal). The aim of this study was to evaluate the performance of these methods in terms of data utility and privacy trade off. Our results showed that CT‐GAN and Avatar used with k = 10 (number of patients used to create the local model of generation) had the best overall performance in terms of data utility and privacy preservation. However, the TVAE method showed a relatively lower level of performance in these aspects. In terms of Hazard ratio estimation, Avatar with k = 10 produced HR estimates closest to the original data, whereas CT‐GAN slightly underestimated the HR and TVAE showed the most significant deviation from the original HR. We also investigated the effect of applying the algorithms multiple times to improve results stability in terms of HR estimation. Our findings suggested that this approach could be beneficial, especially in the case of small datasets, to achieve more reliable and robust results. In conclusion, our study provides valuable insights into the performance of CT‐GAN, TVAE, and Avatar methods for synthetic data generation in pharmacogenetic research. The application to other type of data and analyses (data driven) used in pharmacology should be further investigated. [ABSTRACT FROM AUTHOR]

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 dierent objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss’ Kappa = 0.702), establishing excellent validity and reliability. Videos’ exact timing of motion onset was identified using a custom motion detection frame-dierencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos’ timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framewo. [ABSTRACT FROM AUTHOR]

We report a new image-based inter-analyst study to investigate fission-track grain selection and analysis by 13 participants from an image data set that included grains of variable quality. Results suggest that participants with less experience show a higher rate of selecting unsuitable grains, while participants from the same laboratories generally provide similar results. Less analysis experience may result in the rejection of suitable grains, or inclusion of unsuitable ones. While inappropriate omission and inclusion can both bias results, the latter is more pernicious due to the standard practice of achieving a predecided number of analyses; particularly in difficult samples, there is a danger of "squeezing the rock" by weakening selection criteria. Juxtaposing selected regions of interest (ROIs) on the same grains indicates that zoned grains and grains with inclusions and defects yield varying track density estimates, indicating that ROI placement can be an influential factor. We propose developing image data repositories for global data transparency, a global guidance for fission-track analysis, digital teaching modules, and open science. We also point out the need for new approaches for zeta calibration that include consideration of grain quality, methods of uranium determination, and etching protocols. [ABSTRACT FROM AUTHOR]

Applied linguists are committed to the investigation of language and real‐world problems. While this commitment leads to greater awareness of societal issues within the discipline, there are increasing pressures from societies and academic institutions to ensure that scholarship is available to, or has direct value for, the individuals and communities that are the target of our investigations. It is indeed difficult to enact social change through research when scholarship is not tailored to, and carried out with, the very individuals and communities that are being investigated. This paper attends to this opportunity by asking the following question. How do we engage in more impactful, inclusive, and sustainable research that explicitly involves the individuals and communities that we investigate? I introduce circular applied linguistics to consider the ways in which the discipline can be more impactful, inclusive, and sustainable in its research. I show how circular applied linguistics is based on the mutual benefit and shared knowledge of the researcher and the researched, creating a culture of ethical, open science, and leading to reflexive scholarship, that has greater relevance to societies. [ABSTRACT FROM AUTHOR]

Purpose: This paper explores the different open science policy effects on the knowledge generation process of researchers in basic sciences: biology, chemistry and physics. Design/methodology/approach: This paper uses a qualitative methodology with a content analysis approach. It uses seventeen semi-directed interviews. Findings: The main perceived effect of open science is access to research inputs, with open access, open research data and code reuse as primary sources. Another issue is the increase of collaboration with other colleagues in terms of the ability to collaborate faster and encouraging the exchange of ideas. However, this benefit does not translate to the division of labor in large transnational teams. Time spent on tasks like cleaning up data and code, scooping and other ethical issues are unfavorable aspects noted. Practical implications: Policymakers could use this study to enhance current open science policies in the countries. Originality/value: This study analyzes the perspectives of basic sciences researchers from two countries about open science policies. The main conclusion is the fact that open science policies should focus on the research process itself – rather than research outputs – in order to effectively tackle inequalities in science. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2023-0135 [ABSTRACT FROM AUTHOR]

We argue that researchers should test less, estimate more, and adopt Open Science practices. We outline some of the flaws of null hypothesis significance testing and take three approaches to demonstrating the unreliability of the p value. We explain some advantages of estimation and meta‐analysis ("the new statistics"), especially as contributions to Open Science practices, which aim to increase the openness, integrity, and replicability of research. We then describe esci (estimation statistics with confidence intervals): a set of online simulations and an R package for estimation that integrates into jamovi and JASP. This software provides (a) online activities to sharpen understanding of statistical concepts (e.g., "The Dance of the Means"); (b) effects sizes and confidence intervals for a range of study designs, largely by using techniques recently developed by Bonett; (c) publication‐ready visualisations that make uncertainty salient; and (d) the option to conduct strong, fair hypothesis evaluation through specification of an interval null. Although developed specifically to support undergraduate learning through the 2nd edition of our textbook, esci should prove a valuable tool for graduate students and researchers interested in adopting the estimation approach. Further information is at (https://thenewstatistics.com). [ABSTRACT FROM AUTHOR]

Functional traits offer an informative framework for understanding ecosystem functioning and responses to global change. Trait data are abundant in the literature, yet many communities of practice lack data standards for trait measurement and data sharing, hindering data reuse that could reveal large‐scale patterns in functional and evolutionary ecology. Here, we present a roadmap toward community data standards for trait‐based research on bees, including a protocol for effective trait data sharing. We also review the state of bee functional trait research, highlighting common measurement approaches and knowledge gaps. These studies were overwhelmingly situated in agroecosystems and focused predominantly on morphological and behavioral traits, while phenological and physiological traits were infrequently measured. Studies investigating climate change effects were also uncommon. Along with our review, we present an aggregated morphological trait dataset compiled from our focal studies, representing more than 1600 bee species globally and serving as a template for standardized bee trait data presentation. We highlight obstacles to harmonizing this trait data, especially ambiguity in trait classes, methodology, and sampling metadata. Our framework for trait data sharing leverages common data standards to resolve these ambiguities and ensure interoperability between datasets, promoting accessibility and usability of trait data to advance bee ecological research. [ABSTRACT FROM AUTHOR]

The post-harvest process is important to increasing the market value of limes and requires focus. During this process, limes are graded and categorized based on size, weight, and volume. Therefore, identifying efficient means of estimating these properties is very important and remains an open research area. This study applies the concept of computer vision based on traditional machine learning algorithms (partial least square regression (PLS), epsilon-support vector regression (ε-SVR), decision tree (DT), random forest (RF), adaptive boosting (AB), gradient boosting (GB), Bagging meta-estimator (BME), and extremely randomized trees (ERTs)) and pre-trained deep learning (InceptionV3, MoblieNetV2, ResNet50, and VGG-16) for estimating the weight and volume of limes. Our findings showed that the BME and ResNet50 could yield the highest performance for estimating the weight and volume of limes. The BME produced R test 2 values of 0.954 and 0.882 for weight and volume, respectively, while the R test 2 values of ResNet50 models were between 0.951 and 0.957 for weight and volume, respectively. This study concluded that computer vision based on both traditional machine learning and deep learning could be used to estimate the weight and volume of limes. The approach proposed in this study can be adopted for applications related to computer vision in the post-harvest process. [ABSTRACT FROM AUTHOR]

Open science practices are now at the forefront of discussions in the applied linguistics research community. Proponents of open science argue for its potential to enhance research quality and accessibility while promoting a collaborative and equitable environment. Winke advocates integrating open science into language assessment research to enhance research quality, accessibility, and collaboration. This response introduces two additional perspectives to support open science practices. The first is a framework, which identifies five schools of thought on open science that emphasize understanding the various goals of open science and the scientific methods and tools that are used to pursue them. Second, I highlight two additional characteristics of open science: the need for community and the costs of open science. These additional perspectives underscore the significance of making research processes transparent and inclusive, extending beyond traditional academic boundaries to engage the public and industry stakeholders. By integrating these considerations, this response aims to offer a nuanced view of the challenges and opportunities that open science presents in the field of language assessment, suggesting ideas for how researchers outside and inside the language assessment industry can work toward improving open science practices in language assessment research. [ABSTRACT FROM AUTHOR]

This study is a systematic examination of the open access status of research in two flagship language testing and assessment journals: Language Testing and Language Assessment Quarterly. Coding and analysing 898 articles, we investigated (a) the prevalence of open access in four aspects—open manuscripts, open materials, open data, and open code, and (b) the relationship between open access and various characteristics of research, tests, and researchers. Our study revealed a positive trend in the adoption of open access over time, with open manuscripts and materials showing notable increases. Open code and data have remained scarce, though with a recent uptick from a low base. Notably, logistic regression results suggest inequitable participation in open access as authors from the Global South were less likely to have open manuscripts. Recognising the potential role of flagship journals as trend and standard setters, we call on the field to (a) shift towards more equitable open access models, (b) balance intellectual property concerns with validation needs, (c) recognise open code and open data with protected access via dedicated badges, and (d) adopt Research Transparency Statements, a new reporting structure inclusive of methodological and epistemological differences in open research practices. [ABSTRACT FROM AUTHOR]

Winke delineates objectives and suggests a series of steps for the implementation of Open Science (OS) in language assessment. While we recognize the relevance and potential success of these concrete measures for OS in language assessment, the distinctive challenges confronting OS in China may prevent researchers and practitioners from fully capitalizing on them. In response to Winke, we first reflect on the significant challenges encountered by Chinese language assessment researchers and practitioners. These challenges include the absence of an ethos of openness in language assessment research and practice, difficulties in publishing in scholarly journals, including open-access (OA) journals, and the sensitive nature of the data involved in large-scale, high-stakes language testing. To address these issues and forge ahead, we propose a community-oriented, grassroots-driven approach to cultivating an OS culture and fortifying collaboration among stakeholders. We hope that, through concerted efforts, we can promote OS and, more importantly, enhance the quality of language assessment research and practice in China. [ABSTRACT FROM AUTHOR]

The Open Science movement is taking hold around the world, and language testers are taking part. In this Viewpoint, I discuss how sharing, collaborating, and building trust, guided by Open Science principles, benefit the language testing field. To help more language testers join in, I present a standard definition of Open Science and describe four ways language testing researchers can immediately partake. Overall, I share my views on how Open Science is an accelerating process that improves language testing as a scientific and humanistic field. [ABSTRACT FROM AUTHOR]

To improve data usage in an interdisciplinary context, a clear understanding of the variables being measured is required for both humans and machines. In this paper, the I-ADOPT framework, which decomposes variable names into atomic elements, was tested within the context of continental surfaces and critical zone science, characterized by a large number and variety of observed environmental variables. We showed that the I-ADOPT framework can be used effectively to describe environmental variables with precision and that it was flexible enough to be used in the critical zone science context. Variable names can be documented in detail while allowing alignment with other ontologies or thesauri. We have identified difficulties in modeling complex variables, such as those monitoring fluxes between different environmental compartments and for variables monitoring ratios of physical quantities. We also showed that, for some variables, different decompositions were possible, which could make alignments with other ontologies and thesauri more difficult. The precision of variable names proved inadequate for data discovery services and a non-standard label (SimplifiedLabel) had to be defined for this purpose. In the context of open science and interdisciplinary research, the I-ADOPT framework has the potential to improve the interoperability of information systems and the use of data from various sources and disciplines. [ABSTRACT FROM AUTHOR]

Open research data refer to publicly available scientific information that can be accessed free of charge, usually provided by public data sources. Users must comply with specific requirements set by the institutions providing the data and always acknowledge the source of the data when processing, transmitting, storing or publishing it. One of the tasks of the BrineRIS project is the mapping of brine resources, requiring reliable data on the location of exploration facilities, environmental characteristics, brine exploitation parameters and formal and legal information. These data come from a review of various archives, databases and survey results. Initially, information on the location of the sources should be obtained, which may be available in publicly accessible databases. Next, geological and hydrogeological parameters, which can be obtained from scientific papers and reports, are useful. An important part of the project is also the analysis of legal regulations concerning water extraction and environmental protection. Therefore, data should be obtained from various sources, such as public administration, state institutions or research units. These will serve to develop the database needed to perform further analyses within the BrineRIS research project. It is therefore crucial to carefully collect, analyse and assess the usefulness of the data. [ABSTRACT FROM AUTHOR]

According to the European Data Strategy established in 2020, the European Open Science Cloud (EOSC) is described as "the basis for a science, research and innovation data space... and will be connected and articulated with the sectoral data spaces", being one of the 14 European Common Data Spaces. While current cross-sectoral interactions with the EOSC are realised through the association's Health Data Task Force, advancements in other EU priorities, such as the Green Deal and the Digital Strategy, should be accelerated in the green and digital transitions and integrated by reinforcing each other to be climate-neutral by 2050. With this motivation, this paper systematically reviews data spaces and digital twins (DTs) within the context of research and innovation. Specifically, focusing on the relevance of the EOSC to the Green Deal Data Space (GDDS) and DTs of the Earth, the relationship between them is explored using a topic search with various keyword combinations in the Web of Science and CORDIS databases. Based on the selected scientific articles and projects, collaboration opportunities are mapped to connect relevant stakeholders. Furthermore, existing and developing service components that could contribute to technical building blocks for the GDDS are identified. In summary, key findings are highlighted, addressing the current gaps and opportunities among the GDDS initiatives presented in this review. [ABSTRACT FROM AUTHOR]

This document is a list of references and sources related to various topics in psychology and scientific research. It includes articles, studies, and videos discussing subjects such as the replication crisis in psychology, the credibility of scientific literature, stereotype threat, and the use of preregistration in research. The sources provide diverse perspectives on these topics and can be useful for library patrons conducting research in these areas. [Extracted from the article]

Our comment on Archer's enticing article focuses on his extension of Bhaskar's philosophy to psychology, and on direct replication, which the author says is of very limited use in psychology. We only deal with critical realism indirectly. Our arguments boil down to two points: experiments can usefully be seen as performative (and the same goes for research in general), and replication is not problematic in psychology because of the variability of results, but useful for precisely that reason. Replication studies may even inspire psychologists to accept a wider range of epistemic approaches, although there are reasons to be pessimistic about the likelihood of fundamental change in the discipline. [ABSTRACT FROM AUTHOR]