Standardised Versioning of Datasets: a FAIR-compliant Proposal

This paper presents a standardised dataset versioning framework for improved reusability, recognition and data version tracking, facilitating comparisons and informed decision-making for data usability and workflow integration. The framework adopts a software engineering-like data versioning nomenclature ("major.minor.patch") and incorporates data schema principles to promote reproducibility and collaboration. To quantify changes in statistical properties over time, the concept of data drift metrics (d) is introduced. Three metrics (dP, dE,PCA, and dE,AE) based on unsupervised Machine Learning techniques (Principal Component Analysis and Autoencoders) are evaluated for dataset creation, update, and deletion. The optimal choice is the dE,PCA metric, combining PCA models with splines. It exhibits efficient computational time, with values below 50 for new dataset batches and values consistent with seasonal or trend variations. Major updates (i.e., values of 100) occur when scaling transformations are applied to over 30% of variables while efficiently handling information loss, yielding values close to 0. This metric achieved a favourable trade-off between interpretability, robustness against information loss, and computation time.

Levels of evidence for human system risk evaluation

NASA uses a continuous risk management process to seek out new knowledge of spaceflight-induced risk to human health and performance. The evidence base that informs the risk assessments in this domain is constantly changing as more information is gleaned from a continuous human presence in space and from ongoing research. However, the limitations of this evidence are difficult to characterize because fewer than 700 humans have ever flown in space, and information comes from a variety of sources that span disciplines, including engineering, medicine, food and nutrition, and many other life sciences. The Human System Risk Board (HSRB) at NASA is responsible for assessing risk to astronauts and communicating this risk to agency decision-makers. A critical part of that communication is conveying the uncertainty regarding the understanding of the changes that spaceflight induces in human processes and the complex interactions between humans and the spacecraft. Although the strength of evidence grades is common in the academic literature, these scores are often not useful for the problems of human spaceflight. The HSRB continues to update the processes used to report the levels of evidence. This paper describes recent updates to the methods used to assign the level of evidence scores to the official risk postures and to the causal diagrams used by the HSRB.

Causal diagramming for assessing human system risk in spaceflight

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks that affect astronaut health and performance before, during and after spaceflight. The Human System Risk Board (HSRB) at NASA Johnson Space Center is responsible for setting the official risk posture for each of the human system risks and determining-based on evaluation of the available evidence-when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce spaceflight-induced risk to astronauts. The adverse effects of spaceflight begin at launch and continue throughout the duration of the mission, and in some cases, across the lifetime of the astronaut. Historically, research has been conducted in individual risk "silos" to characterize risk, however, astronauts are exposed to all risks simultaneously. In January of 2020, the HSRB at NASA began assessing the potential value of causal diagramming as a tool to facilitate understanding of the complex causes and effects that contribute to spaceflight-induced human system risk. Causal diagrams in the form of directed acyclic graphs (DAGs) are used to provide HSRB stakeholders with a shared mental model of the causal flow of risk. While primarily improving communication among those stakeholders, DAGs also allow a composite risk network to be created that can be tracked and configuration managed. This paper outlines the HSRB's pilot process for this effort, the lessons learned, and future goals for data-driven risk management approaches.

Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic

Introduction

The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency.

Methods

At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output.

Results

Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19.

Discussion

Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

Integrative and inclusive genomics to promote the use of underutilised crops

Underutilised crops or orphan crops are important for diversifying our food systems towards food and nutrition security. Here, the authors discuss how the development of underutilised crop genomic resource should align with their breeding and capacity building strategies, and leverage advances made in major crops.

rworkflows: automating reproducible practices for the R community

Despite calls to improve reproducibility in research, achieving this goal remains elusive even within computational fields. Currently, >50% of R packages are distributed exclusively through GitHub. While the trend towards sharing open-source software has been revolutionary, GitHub does not have any default built-in checks for minimal coding standards or software usability. This makes it difficult to assess the current quality R packages, or to consistently use them over time and across platforms. While GitHub-native solutions are technically possible, they require considerable time and expertise for each developer to write, implement, and maintain. To address this, we develop rworkflows; a suite of tools to make robust continuous integration and deployment ( https://github.com/neurogenomics/rworkflows ). rworkflows can be implemented by developers of all skill levels using a one-time R function call which has both sensible defaults and extensive options for customisation. Once implemented, any updates to the GitHub repository automatically trigger parallel workflows that install all software dependencies, run code checks, generate a dedicated documentation website, and deploy a publicly accessible containerised environment. By making the rworkflows suite free, automated, and simple to use, we aim to promote widespread adoption of reproducible practices across a continually growing R community.

Developing interdisciplinary research teams in neurosurgery: key elements to success in brachial plexus and peripheral nerve surgery

The highest-impact medical literature is increasingly produced by interdisciplinary teams. The field of neurosurgery, which involves complex pathologies and recoveries, is particularly amenable to interdisciplinary research approaches. However, research in the medical context regarding the characteristics of effective teams, as well as how to develop and maintain interdisciplinary teams, remains lacking. Here, the authors used the business literature to identify the characteristics of effective teams. They then used the University of Michigan Brachial Plexus and Peripheral Nerve Program, founded under the leadership of the late Dr. Lynda Yang, as a case study for how these principles can be applied to build and operationalize a successful interdisciplinary team. They suggest that these same techniques can be used to create interdisciplinary research groups in other areas of neurosurgery.

The EPOS multi-disciplinary Data Portal for integrated access to solid Earth science datasets

The European Plate Observing System (EPOS) is a long-term initiative aimed at integrating research infrastructures for solid Earth science in Europe. EPOS provides a sustainable, multidisciplinary user-oriented platform - the EPOS Data Portal - that facilitates data integration, access, use, and re-use, while adhering to the FAIR principles. The paper describes the key governance, community building, and technical aspects for achieving multidisciplinary data integration through the portal. It also outlines the key portal features for aggregating approximately 250 data sources from more than ten different scientific communities. The main architectural concepts underpinning the portal, namely the rich-metadata, the service-driven data provision, and the usage of semantics, are outlined. The paper discusses the challenges encountered during the creation of the portal, describes the community engagement process, and highlights the benefits to the scientific community and society. Future work includes expanding portal functionalities to include data analysis, processing, and visualization and releasing the portal as an open-source software package.

'Jumping through hoops': A metaphor for early career nurse researchers' experiences and resilience building as international collaborators

AIM

To present and discuss our experiences of learning how to establish and maintain an international collaboration as early career nurse researchers residing in the United States and Australia.

BACKGROUND

International research collaborations require additional startup time given the complexities of navigating cultural differences, obtaining ethics committee approvals in different countries and collecting human subject data. International collaborations may be daunting for early career researchers given their inexperience and pragmatic focus on research projects that lead to outputs achievable on short timelines for career advancement.

DESIGN

Discussion paper.

DATA SOURCES

Evidence from international literature about global collaborations across numerous disciplines, including potential factors that could facilitate or constrain early career researcher efforts to engage in international collaborations, were combined with authors' lived experiences as early career researchers.

DISCUSSION

Our collaboration began in July 2022 through a professional introduction spurred by a call for applications to fund global nursing education collaborations. Interpersonal, logistical and organizational factors played a role in our lived experiences of beginning an international collaboration. Our experiences are consistent with published literature about the time and complexity involved in conducting international research.

CONCLUSION

Investing time building interpersonal relationships strengthens international research and supports collaborative learning and intercultural understanding. These professional relationships can be built over time to develop significant bodies of research with international impact. Early career researchers need to be resilient, persistent and tenacious as they 'jump through hoops' to establish international research collaborations.

IMPACT

Building relationships during international research collaborations supports collaborative learning for intercultural understanding and strengthens research to address emerging global problems. International nursing research collaborations could encourage greater curiosity, innovative ideas and solutions to international problems that could not be achieved in isolation.

PATIENT OR PUBLIC CONTRIBUTION

There was no patient or public involvement in the design and development of this paper.

REPRESENT recommendations: improving inclusion and trust in cancer early detection research

Detecting cancer early is essential to improving cancer outcomes. Minoritized groups remain underrepresented in early detection cancer research, which means that findings and interventions are not generalisable across the population, thus exacerbating disparities in cancer outcomes. In light of these challenges, this paper sets out twelve recommendations to build relations of trust and include minoritized groups in ED cancer research. The Recommendations were formulated by a range of stakeholders at the 2022 REPRESENT consensus-building workshop and are based on empirical data, including a systematic literature review and two ethnographic case studies in the US and the UK. The recommendations focus on: Long-term relationships that build trust; Sharing available resources; Inclusive and accessible communication; Harnessing community expertise; Unique risks and benefits; Compensation and support; Representative samples; Demographic data; Post-research support; Sharing results; Research training; Diversifying research teams. For each recommendation, the paper outlines the rationale, specifications for how different stakeholders may implement it, and advice for best practices. Instead of isolated recruitment, public involvement and engagement activities, the recommendations here aim to advance mutually beneficial and trusting relationships between researchers and research participants embedded in ED cancer research institutions.

Updates to the NASA human system risk management process for space exploration

This paper describes updates to NASA's approach for assessing and mitigating spaceflight-induced risks to human health and performance. This approach continues to evolve to meet dynamically changing risk environments: lunar missions are currently being designed and the ultimate destination will be Mars. Understanding the risks that astronauts will face during a Mars mission will depend on building an evidence base that informs not only how the humans respond to the challenges of the spaceflight environment, but also how systems and vehicles can be designed to support human capabilities and limitations. This publication documents updates to the risk management process used by the Human System Risk Board at NASA and includes changes to the likelihood and consequence matrix used by the board, the design reference mission categories and parameters, and the standardized evaluation of the levels of evidence that the board accepts when setting risk posture. Causal diagramming, using directed acyclic graphs, provides all stakeholders with the current understanding of how each risk proceeds from a spaceflight hazard to a mission-level outcome. This standardized approach enables improved communication among stakeholders and delineates how and where more knowledge can improve perspective of human system risks and which countermeasures can best mitigate these risks.

A dataset for assessing phytolith data for implementation of the FAIR data principles

Phytolith research contributes to our understanding of plant-related studies such as plant use in archaeological contexts and past landscapes in palaeoecology. This multi-disciplinarity combined with the specificities of phytoliths themselves (multiplicity, redundancy, naming issues) produces a wide variety of methodologies. Combined with a lack of data sharing and transparency in published studies, it means data are hard to find and understand, and therefore difficult to reuse. This situation is challenging for phytolith researchers to collaborate from the same and different disciplines for improving methodologies and conducting meta-analyses. Implementing The FAIR Data principles (Findable, Accessible, Interoperable and Reusable) would improve transparency and accessibility for greater research data sustainability and reuse. This paper sets out the method used to conduct a FAIR assessment of existing phytolith data. We sampled and assessed 100 articles of phytolith research (2016-2020) in terms of the FAIR principles. The end goal of this project is to use the findings from this dataset to propose FAIR guidance for more sustainable publishing of data and research in phytolith studies.

Reducing Clinical Trial Monitoring Resources and Costs With Remote Monitoring: Retrospective Study Comparing On-Site Versus Hybrid Monitoring

BACKGROUND

Clinical research associates (CRAs) monitor the progress of a trial, verify the data collected, and ensure that the trial is carried out and reported in accordance with the trial protocol, standard operating procedures, and relevant laws and regulations. In response to monitoring challenges during the COVID-19 pandemic, Peking University Cancer Hospital launched a remote monitoring system and established a monitoring model, combining on-site and remote monitoring of clinical trials. Considering the increasing digitization of clinical trials, it is important to determine the optimal monitoring model for the general benefit of centers conducting clinical trials worldwide.

OBJECTIVE

We sought to summarize our practical experience of a hybrid model of remote and on-site monitoring of clinical trials and provide guidance for clinical trial monitoring management.

METHODS

We evaluated 201 trials conducted by our hospital that used on-site monitoring alone or a hybrid monitoring model, of which 91 trials used on-site monitoring alone (arm A) and 110 used a hybrid model of remote and on-site monitoring (arm B). We reviewed trial monitoring reports from June 20, 2021, to June 20, 2022, and used a customized questionnaire to collect and compare the following information: monitoring cost of trials in the 2 models as a sum of the CRAs' transportation (eg, taxi fare and air fare), accommodation, and meal costs; differences in monitoring frequency; the number of monitored documents; and monitoring duration.

RESULTS

From June 20, 2021, to June 20, 2022, a total of 320 CRAs representing 201 sponsors used the remote monitoring system for source data review and the verification of data from 3299 patients in 320 trials. Arm A trials were monitored 728 times and arm B trials were monitored 849 times. The hybrid model in arm B had 52.9% (449/849) remote visits and 48.1% (409/849) on-site visits. The number of patients' visits that could be reviewed in the hybrid monitoring model increased by 34% (4.70/13.80; P=.004) compared with that in the traditional model, whereas the duration of monitoring decreased by 13.8% (3.96/28.61; P=.03) and the total cost of monitoring decreased by 46.2% (CNY ¥188.74/408.80; P<.001). These differences were shown by nonparametric testing to be statistically significant (P<.05).

CONCLUSIONS

The hybrid monitoring model can ensure timely detection of monitoring issues, improve monitoring efficiency, and reduce the cost of clinical trials and should therefore be applied more broadly in future clinical studies.

Light curves and colours of the ejecta from Dimorphos after the DART impact

On 26 September 2022, the Double Asteroid Redirection Test (DART) spacecraft struck Dimorphos, a satellite of the asteroid 65803 Didymos1. Because it is a binary system, it is possible to determine how much the orbit of the satellite changed, as part of a test of what is necessary to deflect an asteroid that might threaten Earth with an impact. In nominal cases, pre-impact predictions of the orbital period reduction ranged from roughly 8.8 to 17 min (refs. 2,3). Here we report optical observations of Dimorphos before, during and after the impact, from a network of citizen scientists' telescopes across the world. We find a maximum brightening of 2.29 ± 0.14 mag on impact. Didymos fades back to its pre-impact brightness over the course of 23.7 ± 0.7 days. We estimate lower limits on the mass contained in the ejecta, which was 0.3-0.5% Dimorphos's mass depending on the dust size. We also observe a reddening of the ejecta on impact.

A repository for the publication and sharing of heterogeneous materials data

National Materials Data Management and Service platform (NMDMS) is a materials data repository for the publication and sharing of heterogeneous materials scientific data and follows the FAIR principles: Findable, Accessible, Interoperable, and Reusable. To ensure data are 'Interoperable, NMDMS uses a user-friendly semi-structured scientific data model, named dynamic container', to define, exchange, and store heterogeneous scientific data. Then, a personalized yet standardized data submission subsystem, a rigorous project data review and publication subsystem, and a multi-granularity data query and retrieval subsystem collaboratively make data 'Reusable', 'Findable', and 'Accessible'. Finally, China's "National Key R&D Program: Material Genetic Engineering Key Special Project" has adopted NMDMS to publish and share its project data. There are 12,251,040 pieces of data published in NMDMS since 2018, under 87 categories and 1,912 user-defined schemas from 45 projects. The platform has been accessed 908875 times, and 2403,208 pieces of data have been downloaded. In short, NMDMS effectively accelerates the publication and sharing of material project data in China.

Rethinking clinical study data: why we should respect analysis results as data

The development and approval of new treatments generates large volumes of results, such as summaries of efficacy and safety. However, it is commonly overlooked that analyzing clinical study data also produces data in the form of results. For example, descriptive statistics and model predictions are data. Although integrating and putting findings into context is a cornerstone of scientific work, analysis results are often neglected as a data source. Results end up stored as "data products" such as PDF documents that are not machine readable or amenable to future analyses. We propose a solution to "calculate once, use many times" by combining analysis results standards with a common data model. This analysis results data model re-frames the target of analyses from static representations of the results (e.g., tables and figures) to a data model with applications in various contexts, including knowledge discovery. Further, we provide a working proof of concept detailing how to approach standardization and construct a schema to store and query analysis results.

Making European performance and impact assessment frameworks for research infrastructures glocal

Sustainability of research infrastructures (RIs) is a big challenge for funders, stakeholders and operators, and the development and adoption of adequate management tools is a major concern, namely tools for monitoring and evaluating their performance and impact. BioData.pt is the Portuguese Infrastructure of Biological data and the Portuguese node of the European Strategy Forum on Research Infrastructures "Landmark" ELIXIR. The foundations of this national research infrastructure were laid under the "Building BioData.pt" project, for four years. During this period, performance and impact indicators were collected and analysed under the light of international guidelines for assessing the performance and impact of European research infrastructures produced by the European Strategy Forum on Research Infrastructures, the Organisation for Economic Co-operation and Development and the EU-funded RI-PATHS project. The exercise shared herein showed that these frameworks can be adopted by national RIs, with the necessary adaptations, namely to reflect the national landscape and specificity of activities, and can be powerful tools in supporting the management of RIs. "Not everything that counts can be counted, and not everything that can be counted, counts". (Attributed to William Bruce Cameron).

Making European performance and impact assessment frameworks glocal

Sustainability of research infrastructures (RIs) is a big challenge for funders, stakeholders and operators, and the development and adoption of adequate management tools is a major concern, namely tools for monitoring and evaluating their performance and impact. BioData.pt is the Portuguese Infrastructure of Biological and Portuguese node of the European Strategy Forum on Research Infrastructures "Landmark" ELIXIR. The foundations of this national research infrastructure were laid under the "Building BioData.pt" project, for four years. During this period, performance and impact indicators were collected and analysed under the light of international guidelines for assessing the performance and impact of European research infrastructures produced by the European Strategy Forum on Research Infrastructures, the Organisation for Economic Co-operation and Development and the EU-funded RI-PATHS project. The exercise shared herein showed that these frameworks can be adopted by national RIs, with the necessary adaptations, namely to reflect the national landscape and specificity of activities, and can be powerful tools in supporting the management of RIs. "Not everything that counts can be counted, and not everything that can be counted, counts". Albert Einstein, Theoretical physicist and Nobel Prize winner.

An urgent call to raise the bar in oncology

Important breakthroughs in medical treatments have improved outcomes for patients suffering from several types of cancer. However, many oncological treatments approved by regulatory agencies are of low value and do not contribute significantly to cancer mortality reduction, but lead to unrealistic patient expectations and push even affluent societies to unsustainable health care costs. Several factors that contribute to approvals of low-value oncology treatments are addressed, including issues with clinical trials, bias in reporting, regulatory agency shortcomings and drug pricing. With the COVID-19 pandemic enforcing the elimination of low-value interventions in all fields of medicine, efforts should urgently be made by all involved in cancer care to select only high-value and sustainable interventions. Transformation of medical education, improvement in clinical trial design, quality, conduct and reporting, strict adherence to scientific norms by regulatory agencies and use of value-based scales can all contribute to raising the bar for oncology drug approvals and influence drug pricing and availability.

Global snapshot of the effects of the COVID-19 pandemic on the research activities of materials scientists between Spring and Autumn 2020

We conducted a global survey on the effects of the COVID-19 pandemic on the research activities of materials scientists by distributing a questionnaire on 9 October 2020 with a response deadline of 23 October 2020. The questions covered issues such as access to labs, effectiveness of online conferences, and effects on doctoral students for the period covering the first lockdowns until the relaxation of restrictions in late September 2020 in many countries. The survey also included online interviews with eminent materials scientists who shared their local experiences during this period. The interviews were compiled as a series of audio conversations for The STAM Podcast that is freely available worldwide. Our findings included that the majority of institutes were not prepared for such a crisis; researchers in China, Japan, and Singapore were able to resume research much quicker - for example after approximately one month in Japan - than their counterparts in the US and Europe after the first lockdowns; researchers adapted to using virtual teleconferencing to maintain contact with colleagues; and doctoral students were the hardest hit by the pandemic with deep concerns about completing their research and career prospects. We hope that the analysis from this survey will enable the global materials science community to learn from each other's experiences and move forward from the unprecedented circumstances created by the pandemic.

Management of a High-Performing Mental Health Recovery Research Group

A personal perspective is given on the processes involved in managing and sustaining a high-performing mental health recovery research group. The broader context of scholarship in the United Kingdom is outlined, in which academic productivity is commodified specifically in relation to peer-reviewed journal papers. Four leadership choices in developing a high-performing research group are discussed: optimal group size; sharing the workload; maintaining a programmatic focus; and performance expectations. Approaches to maximising innovation are identified, including emotional and intellectual engagement of team members, working with diverse stakeholders and convening communities of practice. We use a highly managed approach to publications from inception to acceptance, which is described in detail. The use of these approaches is illustrated in relation to the Recovery Research Team which was formed in 2009. Specific recovery-related issues covered include demonstrating the ability to develop a significant recovery research portfolio (our four current large [>UK£2 m] studies relate to recovery narratives, global mental health peer support work, digital interventions and Recovery Colleges); the positive implications of actively recruiting researchers with mental health lived experience; how performance issues are managed; our approach to involving lived experience co-authors in papers; and our decision to conduct mixed-methods rather than solely qualitative studies.

Substrate-dependent fish have shifted less in distribution under climate change

Analyses of the impacts of climate change on fish species have primarily considered dynamic oceanographic variables that are the output of predictive models, yet fish species distributions are determined by much more than just variables such as ocean temperature. Functionally diverse species are differentially influenced by oceanographic as well as physiographic variables such as bottom substrate, thereby influencing their ability to shift distributions. Here, we show that fish species distributions that are more associated with bottom substrate than other dynamic environmental variables have shifted significantly less over the last 30 years than species whose distributions are associated with bottom salinity. Correspondingly, species whose distributions are primarily determined by bottom temperature or ocean salinity have shifted their mean centroid and southern and northern range boundaries significantly more than species whose distributions are determined by substrate or depth. The influence of oceanographic versus static variables differs by species functional group, as benthic species distributions are more associated with substrate and they have shifted significantly less than pelagic species whose distributions are primarily associated with ocean temperatures. In conclusion, benthic fish, that are more influenced by substrate, may prove much less likely to shift distributions under future climate change.

An analecta of visualizations for foodborne illness trends and seasonality

Disease surveillance systems worldwide face increasing pressure to maintain and distribute data in usable formats supplemented with effective visualizations to enable actionable policy and programming responses. Annual reports and interactive portals provide access to surveillance data and visualizations depicting temporal trends and seasonal patterns of diseases. Analyses and visuals are typically limited to reporting the annual time series and the month with the highest number of cases per year. Yet, detecting potential disease outbreaks and supporting public health interventions requires detailed spatiotemporal comparisons to characterize spatiotemporal patterns of illness across diseases and locations. The Centers for Disease Control and Prevention's (CDC) FoodNet Fast provides population-based foodborne-disease surveillance records and visualizations for select counties across the US. We offer suggestions on how current FoodNet Fast data organization and visual analytics can be improved to facilitate data interpretation, decision-making, and communication of features related to trend and seasonality. The resulting compilation, or analecta, of 436 visualizations of records and codes are openly available online.

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.

Low replicability can support robust and efficient science

There is a broad agreement that psychology is facing a replication crisis. Even some seemingly well-established findings have failed to replicate. Numerous causes of the crisis have been identified, such as underpowered studies, publication bias, imprecise theories, and inadequate statistical procedures. The replication crisis is real, but it is less clear how it should be resolved. Here we examine potential solutions by modeling a scientific community under various different replication regimes. In one regime, all findings are replicated before publication to guard against subsequent replication failures. In an alternative regime, individual studies are published and are replicated after publication, but only if they attract the community's interest. We find that the publication of potentially non-replicable studies minimizes cost and maximizes efficiency of knowledge gain for the scientific community under a variety of assumptions. Provided it is properly managed, our findings suggest that low replicability can support robust and efficient science.

Engaging with research impact assessment for an environmental science case study

Impact assessment is embedded in many national and international research rating systems. Most applications use the Research Impact Pathway to track inputs, activities, outputs and outcomes of an invention or initiative to assess impact beyond scholarly contributions to an academic research field (i.e., benefits to environment, society, economy and culture). Existing approaches emphasise easy to attribute 'hard' impacts, and fail to include a range of 'soft' impacts that are less easy to attribute, yet are often a dominant part of the impact mix. Here, we develop an inclusive 3-part impact mapping approach. We demonstrate its application using an environmental initiative.

Challenges of international oncology trial collaboration-a call to action

International collaboration in oncology trials has the potential to enhance clinical trial activity by expediting the recruitment of large patient populations, testing treatments in diverse populations and facilitating the study of rare tumours or specific molecular subtypes. However, a number of challenges continue to hinder the efficient and productive conduct of both commercial and non-commercial international clinical trials. These challenges include complex and burdensome regulatory requirements, the high cost of conducting trials, and logistical challenges associated with ethics review, drug supply and biospecimen collection and management. We propose solutions to promote oncology trial collaboration, such as regulatory reform, harmonisation of trial initiation and management processes and greater recognition and funding of academic (non-commercial) clinical trials. It is only through coordinated effort and leadership from researchers, regulators and those responsible for health systems that the full potential of international trial collaboration can be realised.

EEG-BIDS, an extension to the brain imaging data structure for electroencephalography

The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard.

Closing the barrier between disease and health outcomes in Africa through research and capacity development

BACKGROUND

While the burden of disease in Africa is high, health research emanating from the continent is low. Building human capacity and research infrastructure to close the gap between research and disease is thus of great imporatance.

OBJECTIVE

In order to improve research outputs and postgraduate training in the Faculty of Health Sciences, University of the Witwatersrand, the Health Sciences Research Office put in place a series of strategic initiatives over time.

METHODS

A range of strategic activities, for both postgraduate students and academic staff, were developed in parallel and sequentially over a period of approximately nine years (2008-2016). The latter years were a time of consolidation of the programmes. Outcomes of these activities were 'measured' by increases in publications, decreases in time to graduation and enrichment of the research environment.

RESULTS

A doubling of research publications and an increase in citations occurred over the period under review. In addition, there was a decrease in the time postgraduate students took to graduate.

CONCLUSIONS

A varied, but structured research management plan may be of value in African and other developing health sciences institutions to enable the increase in research outputs and capacity development, desperately needed to close the barrier between disease and health.

High-quality science requires high-quality open data infrastructure

Resources for data management, discovery and (re)use are numerous and diverse, and more specifically we need data resources that enable the FAIR principles1 of Findability, Accessibility, Interoperability and Reusability of data.

The Future of Dental Schools in Research Universities and Academic Health Centers

As a profession, dentistry is at a point of discernible challenge as well as incredible opportunity in a landscape of evolving changes to health care, higher education, and evidence-based decision making. Respecting the past yet driving forward, a well-mapped future course is critical. Orchestrating this course in a collaborative manner is essential for the visibility, well-being, and potentially the existence of the dental profession. The research performed in dental institutions needs to be contemporary, aligned with biomedical science in general, and united with other disciplines. Dentistry is at risk of attrition in the quality of its research and discovery mission if participation with bioscience colleagues in the collaborative generation of new knowledge is underoptimized. A fundamental opportunity dentistry has is to contribute via its position in academic health centers. Rigorous research as to the impact of interprofessional education and collaborative care on population health outcomes provides significant potential for the dental profession to participate and/or lead such evidence-centered efforts. It is imperative that academic dental institutions are part of interdisciplinary and transdisciplinary organizations that move health care into its new day. Strategizing diversity by bringing together people who have different ways of seeing problems to share perspectives, heuristics, interpretations, technologies, and predictive models across disciplines will lead to impactful progress. Academic dental institutions are a natural part of an emphasis on translational research and acceleration of implementing new scientific discoveries. Dentistry needs to remain an essential and integrated component of higher education in the health professions; doing so necessitates deliberate, respectful, and committed change. This article was written as part of the project "Advancing Dental Education in the 21^st Century."

The Origin and Impact of Ideals in eHealth Research: Experiences From the U-CARE Research Environment

Background

The prevalence of information technology (IT) in society is a foundation for new modes of interaction between patients and health specialists. IT plays an important role in the renewal of care. Several countries have incorporated eHealth plans into their national health strategies. Part of the eHealth evolution concerns Internet psychological treatment and psychosocial care. These interventions are complex to design and evaluate due to legal, ethical, organizational, technical, and methodological challenges.

Objective

The objective of our study was to seek to make explicit contributions to the understanding of ideals in eHealth research, and illuminate their implications for establishing an effective research environment. Our analysis draws from three years of experience in establishing an eHealth research environment, and the literature.

Methods

We worked inductively to characterize challenging research ideals, and their origins, in our environment. Thereafter, we made a selective search of the literature to scrutinize and illuminate each ideal and it’s implications.

Results

In this work, we propose a structured approach to address ideals in eHealth research. The scrutinized ideals are accountability, innovation, rigor, relevance, and sustainability. The approach supports researchers to systematically understand the ideals, their origin, and to manage their implications within an eHealth research environment.

Conclusions

The complexity of eHealth research causes a need for sustainable, multi-disciplinary research environments. There is a need for a structured approach to organize eHealth research. The proposed approach helps to systematically scrutinize ideals, thus promoting high quality research.