Open Science Approach Research Articles

Participatory Mapping: A Systematic Review and Open Science Framework for Future Research

Participatory mapping emerged from a need for more inclusive methods of collecting spatial data with the intention of democratizing the decision-making process. It encompasses a range of methods including mental mapping, sketch mapping, and participatory geographic information systems. There has been a rapid increase in uptake of participatory mapping, but the multidisciplinary nature of the field has resulted in a lack of consistency in the conducting and reporting of research, limiting further development. In this article, we argue that an open science approach is required to enable the field to advance, increasing transparency and replicability in how participatory mapping research is both conducted and reported. This argument is supported by the first large-scale systematic review of the field, which identifies specific areas within participatory mapping that would benefit from an open science approach. Four questions are used to explore the sample: (1) How are different participatory mapping methods being used and reported? (2) What information is given on the data collected through participatory mapping? (3) How are participant demographics being recorded? (4) Who is conducting the research, and where is it being published? From a total of 578 academic research articles, we analyzed a stratified sample of 117. The review reveals a significant lack of reporting on key details in the data collection process, restricting the transparency, replicability, and transferability of participatory mapping research and demonstrating the urgent need for an open science approach. Recommendations are then drawn from the results to guide the design of future participatory mapping research.

Unravelling the Stability of Nightingale Song Over Time and Space Using Open, Citizen Science and Shared Data

Open science approaches enable and facilitate the investigation of many scientific questions in bioacoustics, such as studies on the temporal and spatial evolution of song, as in vocal dialects. In contrast to previous dialect studies, which mostly focused on songbird species with a small repertoire, here we studied the common nightingale (Luscinia megarhynchos), a bird species with a complex and large repertoire. To study dialects on the population level in this species, we used recordings from four datasets: an open museum archive, a citizen science platform, a citizen science project, and shared recordings from academic researchers. We conducted the to date largest temporal and geographic dialect study of birdsong including recordings from 1930 to 2019 and from 13 European countries, with a geographical coverage of 2,652 km of linear distance. To examine temporal stability and spatial dialects, a catalog of 1,868 song types of common nightingales was created. Instead of dialects, we found a high degree of stability over time and space in both, the sub-categories of song and in the occurrence of song types. For example, the second most common song type in our datasets occurred over nine decades and across Europe. In our case study, open and citizen science data proved to be equivalent, and in some cases even better, than data shared by an academic research group. Based on our results, we conclude that the combination of diverse and open datasets was particularly useful to study the evolution of song in a bird species with a large repertoire.

Temporal discounting across adulthood: A systematic review and meta-analysis.

A number of developmental theories have been proposed that make differential predictions about the links between age and temporal discounting, or the devaluation of future rewards. Most empirical studies examining adult age differences in temporal discounting have relied on economic intertemporal choice tasks, which pit choosing a smaller, sooner monetary reward against choosing a larger, later one. Although initial studies using these tasks suggested older adults discount less than younger adults, follow-up studies provided heterogeneous, and thus inconclusive, results. Using an open science approach, we test the replicability of adult age differences in temporal discounting by conducting a preregistered systematic literature search and meta-analysis of adult age differences in intertemporal choice tasks. Across 37 cross-sectional studies (Total N = 104,737), a planned meta-analysis found no sizeable relation between age and temporal discounting, r = -0.068, 95% CI [-0.170, 0.035]. We also found little evidence of publication bias or p-hacking. Exploratory analyses of moderators found no effect of research design (e.g., extreme-group vs. continuous age), incentives (hypothetical vs. real rewards), duration of delay (e.g., days, weeks, months, or years), or quantification of discounting behavior (e.g., proportion of immediate choices vs. parameters from computational modeling). Additional analyses of 12 participant-level data sets found little support for a nonlinear relation between age and temporal discounting across adulthood. Overall, the results suggest that younger, middle-aged, and older adults show similar preferences for smaller, sooner over larger, later rewards. We provide recommendations for future empirical work on temporal discounting across the adult life span. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

ManyBirds: A multi-site collaborative Open Science approach to avian cognition and behavior research

Comparative cognitive and behavior research aims to investigate cognitive evolution by comparing performance in different species to understand how these abilities have evolved. Ideally, this requires large and diverse samples; however, these can be difficult to obtain by single labs or institutions, leading to potential reproducibility and generalization issues with small, less representative samples. To help mitigate these issues, we are establishing a multi-site collaborative Open Science approach called ManyBirds, with the aim of providing new insight into the evolution of avian cognition and behavior through large-scale comparative studies, following the lead of exemplary ManyPrimates, ManyBabies and ManyDogs projects. Here, we outline a) the replicability crisis and why we should study birds, including the origin of modern birds, avian brains and convergent evolution of cognition; b) the current state of the avian cognition field, including a ‘snapshot’ review; c) the ManyBirds project, with plans, infrastructure, limitations, implications and future directions. In sharing this process, we hope that this may be useful for other researchers in devising similar projects in other taxa, like non-avian reptiles or mammals, and to encourage further collaborations with ManyBirds and related ManyX projects. Ultimately, we hope to promote collaboration between ManyX projects to allow for wider investigation of the evolution of cognition across all animals, including potentially humans.

Mapping the State of the Art to Envision the Future of Large-Scale Citizen Science Projects: An Interpretive Review

Citizen science, i.e. citizens’ involvement in research activities, is achieving an increasing re-levance across disparate scientific domains. However, literature is not consistent in arguing citizen science’s attributes and implications when large-scale projects are concerned. The paper systematizes extant scientific knowledge in this field and identifies avenues for further deve-lopments through a bibliometric analysis and an interpretive review. Various approaches to citizen science are implemented to engage citizens in scientific research. They can be located in a continuum composed of two extremes: a contributory approach, which serves research institutions’ needs, and an open science approach, which focuses on citizens’ active participation in knowledge co-creation. Although contributory citizen science paves the way for participatory science, it falls short in empowering citizens, which is central in the open science approach. Interventions aimed at enabling citizens to have an active role in co-creating knowledge in a perspective of science democratization are key to overcoming the understanding of citizen science as a low-cost model of scientific research and to boost the transition towards an open science approach.

An open science and open data approach for the statistically robust estimation of forest disturbance areas

Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717±716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (744) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time.

The benefits of an open-science approach in student research projects

Open science is a movement to allow scientific information, data and outputs to be more widely accessible and reusable, with the active engagement of all the stakeholders. Open science can also describe openness within a research group where all participants share their data, analysis code, ideas and feedback. These ideas can be applied to all aspects of science, from large research consortia to student projects. With great accessibility comes greater reproducibility, leading to better code quality and better research. Here we describe what we have learned and gained from taking an open-science approach in undergraduate and masters student research projects, from the perspective of the student, the day-to-day supervisor, and the principal investigator (PI) or research group leader. We argue for the importance of clear expectations, communication, documentation, and of modelling collaborative behaviour. To design a good student project, we recommend planning the project outcomes so that everybody wins, and planning a pathway from novice to expert within the project.

Light potentials of photosynthetic energy storage in the field: what limits the ability to use or dissipate rapidly increased light energy?

The responses of plant photosynthesis to rapid fluctuations in environmental conditions are critical for efficient conversion of light energy. These responses are not well-seen laboratory conditions and are difficult to probe in field environments. We demonstrate an open science approach to this problem that combines multifaceted measurements of photosynthesis and environmental conditions, and an unsupervised statistical clustering approach. In a selected set of data on mint (Mentha sp.), we show that ‘light potentials’ for linear electron flow and non-photochemical quenching (NPQ) upon rapid light increases are strongly suppressed in leaves previously exposed to low ambient photosynthetically active radiation (PAR) or low leaf temperatures, factors that can act both independently and cooperatively. Further analyses allowed us to test specific mechanisms. With decreasing leaf temperature or PAR, limitations to photosynthesis during high light fluctuations shifted from rapidly induced NPQ to photosynthetic control of electron flow at the cytochrome b6f complex. At low temperatures, high light induced lumen acidification, but did not induce NPQ, leading to accumulation of reduced electron transfer intermediates, probably inducing photodamage, revealing a potential target for improving the efficiency and robustness of photosynthesis. We discuss the implications of the approach for open science efforts to understand and improve crop productivity.

Reaping the benefits of open science in scholarly communication

Regardless of multiple efforts carried out across many countries to disseminate the ideas and the practice of open science, most scholars in the early 2020s do not self-archive their research articles and do not publish research papers in preprint form. Having received no education and training on open science, researchers are often puzzled on what to do, in practice, to start reaping the benefits of open science. This study offers a succinct vademecum on how to benefit from the open science approach to scholarly communication, no matter whether in natural or in humanistic and social sciences.

Massively collaborative crowdsourced research on COVID19 and the chemical senses: Insights and outcomes

In March 2020, the Global Consortium of Chemosensory Research (GCCR) was founded by chemosensory researchers to address emerging reports of unusual smell and taste dysfunction arising from the SARS-CoV-2 pandemic. Over the next year, the GCCR used a highly collaborative model, along with contemporary Open Science practices, to produce multiple high impact publications on chemosensation and COVID19. This invited manuscript describes the founding of the GCCR, the tools and approaches it used, and a summary of findings to date. These findings are contextualized within a summary of some of the broader insights about chemosensation (smell, taste, and chemesthesis) and COVID19 gained over the last 18 months, including potential mechanisms of loss. Also, it includes a detailed discussion of some current Open Science approaches and practices used by the GCCR to increase transparency, rigor, and reproducibility.

High-Fidelity Agent-Based Modeling to Support Prevention Decision-Making: an Open Science Approach

Preventing adverse health outcomes is complex due to the multi-level contexts and social systems in which these phenomena occur. To capture both the systemic effects, local determinants, and individual-level risks and protective factors simultaneously, the prevention field has called for adoption of system science methods in general and agent-based models (ABMs) specifically. While these models can provide unique and timely insight into the potential of prevention strategies, an ABM’s ability to do so depends strongly on its accuracy in capturing the phenomenon. Furthermore, for ABMs to be useful, they need to be accepted by and available to decision-makers and other stakeholders. These two attributes of accuracy and acceptability are key components of open science. To ensure the creation of high-fidelity models and reliability in their outcomes and consequent model-based decision-making, we present a set of recommendations for adopting and using this novel method. We recommend ways to include stakeholders throughout the modeling process, as well as ways to conduct model verification, validation, and replication. Examples from HIV and overdose prevention work illustrate how these recommendations can be applied.

EnTIRE: Mapping Normative Frameworks for EThics and Integrity of REsearch

Background: The areas of Research Ethics and Research Integrity (RE+RI) are rapidly evolving. In the EU and internationally, new legislation, codes of conduct and good practices are constantly being developed. New technologies (e.g. gene editing), complex statistical methods (e.g. biostatistics), pressure to publish and obtain grants, and growing emphasis on stakeholder driven science (e.g. public-private partnerships) increase the complexity of conducting science. In this complex and dynamic environment, researchers cannot easily identify the correct rules and best tools for responsible conduct of research. This also increasingly constitutes a challenge for RE+RI experts. Aim: Our aim is to create a platform that makes the normative framework governing RE+RI easily accessible, supports application in research and evaluation, and involves all stakeholders in a participatory way, thus achieving sustainability. The platform will foster uptake of ethical standards and responsible conduct of research, and ultimately support research excellence and strengthen society’s confidence in research and its findings. Vision: Our vision is that in order to make the normative framework governing RE+RI accessible, a dynamic online Wiki-platform, owned by the community of RE+RI stakeholders, is needed. The value of this platform will lie in the availability of practical information on how to comply with EU, national and discipline-specific RE+RI standards and legislation, including information on rules and procedures, educational materials, and illustrative cases and scenarios. Adopting open science (open source and open data) approaches, the platform will be easy to use, by applying novel techniques for data collection and comparison, enabling users to navigate quickly and intuitively to appropriate content. In order to keep the platform up-to-date and sustainable, it will be based upon active involvement of the RE+RI community, and will contribute to further development of this community by providing a podium for reflection and dialogue on RE+RI norms and practices. Objectives: EnTIRE’s work packages (WP) will: undertake an in-depth stakeholder consultation across EU countries exploring RE+RI experiences and practices in order to define the boundaries of data to be collected, and developing a mapping structure adapted to user needs (WP 2); assemble the relevant normative elements, including RE+RI rules and procedures, educational materials, and illustrative casuistry, and identify relevant institutions across EU countries (WP 3-5); develop a user-friendly Wiki-platform and online resources to foster and facilitate responsible research practices and to promote compliance amongst European researchers with RE+RI standards and pertinent legislation and regulations (WP 6); and foster further development of the RE+RI community, that will support the platform and be supported by it, will keep the information up-to-date, disseminate the project’s findings and develop innovative strategies for maintaining the platform and building relationships to relevant organisations for further dissemination, including sustainable funding (WP 7). Relevance to the work programme: The proposed project responds directly to the core requirement of call SwafS-16-2016 to ‘provide a dynamic mapping of the RE+RI normative framework which applies to scientific research conducted in the EU and beyond’. Our proposal does this by using a participatory approach, stimulating knowledge transfer regarding codes and regulations, resources and institutions, and cases, by applying innovative ICT solutions and open science approaches, and by further developing a community of active users, to enable sustainability after the end of the project.

Limitations and gaps in global bat wing morphology trait data

Abstract Species’ life‐history traits have a wide variety of applications in ecological and conservation research, particularly when assessing threats. The development and growth of global species’ trait databases are critical for improving trait‐based analyses; however, it is vital to understand the gaps and biases in the available data. We reviewed bat wing morphology data, specifically mass, wingspan, wing area, wing loading, and aspect ratio, to identify issues with data reporting and ambiguity. Additionally, we aimed to assess taxonomic and geographic biases in trait data coverage. We found that most studies used similar field methodology, but that data reporting and quality were inconsistent/poor. Additionally, we noted several issues regarding semantic ambiguity in trait definitions, specifically around what constitutes wing area. Globally, we found that bat wing morphology trait coverage was low. Only six bat families had ≥40% trait coverage, and, of those, none consisted of more than 11 species in total. We found similar biases in trait coverage across International Union for Conservation of Nature Red List categories, with threatened species having lower coverage. Geographically, North America, Europe, and the Indomalayan regions exhibited higher overall trait coverage, while both the Afrotropical and Neotropical ecoregions showed poor trait coverage. The underlying biases and gaps in bat wing morphology data have implications for researchers conducting global trait‐based assessments. Implementing imputation techniques may address missing data, but only for smaller regional subsets with substantial trait coverage. Due to generally low overall trait coverage, increasing species’ representation in the database should be prioritised. We suggest adopting an Ecological Trait Standard Vocabulary to reduce semantic ambiguity in bat wing morphology traits, to improve data compilation and clarity. Additionally, we advocate that researchers adopt an Open Science approach to facilitate the growth of a bat wing morphology trait database.

Development of best practices in physiologically based pharmacokinetic modeling to support clinical pharmacology regulatory decision-making-A workshop summary.

Development of best practices in physiologically based pharmacokinetic modeling to support clinical pharmacology regulatory decision-making-A workshop summary.

COPERNICUS AND THE ENERGY CHALLENGE

Abstract. The energy sector will drastically change in the following years; multiple agreements have been signed by countries with the purpose to reduce carbon emission and contain the global temperature increase. Besides, in the next years the energy demand will increase with the growth of the Information and Communications Technology sector. To combine these two aspects, future energy needs to be produced with renewable resources and less with fossil fuels. An opportunity to discover and plan the use of renewable energy resources are geospatial data derived from satellite acquisitions. The European Earth Observation programme Copernicus provides multiple datasets in an Open Science approach. Within this paper, multiple datasets offered by Copernicus services are presented in relation to their exploitation for the energy system analysis, with a particular attention to renewable energy. The datasets will be analysed according to their properties and possibility of usage. Additional Copernicus satellite derived data that can benefit the emerging topic of the food-energy-water nexus are finally presented to point out significant development in the energy sector which is recently claiming growing attention.

An Open Science approach to infer fishing activity pressure on stocks and biodiversity from vessel tracking data

Vessel tracking data help study the potential impact of fisheries on biodiversity and produce risk assessments. Existing workflows process vessel tracks to identify fishing activity and integrate information on species vulnerability. However, there are significant data integration challenges across the data sources needed for an integrated impact assessment due to heterogeneous nomenclatures, data accessibility issues, geographical and computational scalability of the processes, and confidentiality and transparency towards decision making authorities.This paper presents an Open Science data integration approach to use vessel tracking data in integrated impact assessments. Our approach combines heterogeneous knowledge sources from fisheries, biodiversity, and environmental observations to infer fishing activity and risks to potentially impacted species. An Open Science e-Infrastructure facilitates access to data sources and maximises the reproducibility of the results and the method's reusability across several application domains.Our method's quality is assessed through three case studies: The first demonstrates cross-dataset consistency by comparing the results obtained from two different vessel data sources. The second performs a temporal pattern analysis of fishing activity and potentially impacted species over time. The third assesses the potential impact of reduced fishing pressure on marine biodiversity and threatened species due to the 2020 COVID-19 lockdown in Italy. The method is meant to be integrated with other systems through its Open Science-oriented features and can rapidly use new sources of findable, accessible, interoperable, and reusable (FAIR) data. Other systems can use it to (i) classify vessel activity in data-limited scenarios, (ii) identify bycatch species (when catchability data are available), and (iii) study the effects of fisheries on habitats and populations’ growth.

Implementing open science in a daily routine: Team contribution from the Laboratory for Translational Breast Cancer Research

In order to ensure a comprehensive open science approach, the Laboratory for Translational Breast Cancer Research (LTBCR) is developing tools and a working environment that guarantee research integrity, reproducibility, and open access, while respecting GDPR.

Standardized and reproducible measurement of decision-making in mice.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.

SP-013 - Leveraging an open science approach for PET radiotracer discovery: radiolabelling and preliminary neuroimaging of 11C-labelled activin receptor-like kinase 2 inhibitors

SP-013 - Leveraging an open science approach for PET radiotracer discovery: radiolabelling and preliminary neuroimaging of 11C-labelled activin receptor-like kinase 2 inhibitors

Leveraging Open Science Drug Development for PET: Preliminary Neuroimaging of 11C-Labeled ALK2 Inhibitors.

Mutations in the gene encoding activin receptor-like kinase 2 (ALK2) are implicated in the pathophysiology of a pediatric brainstem cancer, diffuse intrinsic pontine glioma (DIPG). Inhibitors of ALK2 that cross the blood–brain barrier have been proposed as a method of treatment for DIPG. As part of an open science approach to radiopharmaceutical and drug discovery, we developed 11C-labeled radiotracers from potent and selective lead ALK2 inhibitors to investigate their brain permeability through positron emission tomography (PET) neuroimaging. Four radiotracers were synthesized by 11C-methylation and assessed by dynamic PET imaging in healthy Sprague–Dawley rats. One of the compounds, [11C]M4K2127, showed high initial brain uptake (SUV ∼ 2), including in the region of interest (pons). This data supports the use of this chemotype as a brain penetrant ALK2 inhibitor that permeates evenly into the pons with potential application for the treatment of DIPG.