scholarly journals Born-Open Data for E-Prime

2020 ◽  
Author(s):  
Denis Cousineau

Born-Open Data experiments are encouraged for better open science practices. To be adopted, Born-Open data practices must be easy to implement. Herein, I introduce a package for E-Prime such that the data files are automatically saved on a GitHub repository. The BornOpenData package for E-Prime works seamlessly and performs the upload as soon as the experiment is finished so that there is no additional steps to perform beyond placing a package call within E-Prime. Because E-Prime files are not standard tab-separated files, I also provide an R function that retrieves the data directly from GitHub into a data frame ready to be analyzed. At this time, there are no standards as to what should constitute an adequate open-access data repository so I propose a few suggestions that any future Born-Open data system could follow for easier use by the research community.

2021 ◽  
Author(s):  
Samir Das ◽  
Rida Abou-Haidar ◽  
Henri Rabalais ◽  
Sonia Denise Lai Wing Sun ◽  
Zaliqa Rosli ◽  
...  

AbstractIn January 2016, the Montreal Neurological Institute-Hospital (The Neuro) declared itself an Open Science organization. This vision extends beyond efforts by individual scientists seeking to release individual datasets, software tools, or building platforms that provide for the free dissemination of such information. It involves multiple stakeholders and an infrastructure that considers governance, ethics, computational resourcing, physical design, workflows, training, education, and intra-institutional reporting structures. The C-BIG repository was built in response as The Neuro’s institutional biospecimen and clinical data repository, and collects biospecimens as well as clinical, imaging, and genetic data from patients with neurological disease and healthy controls. It is aimed at helping scientific investigators, in both academia and industry, advance our understanding of neurological diseases and accelerate the development of treatments. As many neurological diseases are quite rare, they present several challenges to researchers due to their small patient populations. Overcoming these challenges required the aggregation of datasets from various projects and locations. The C-BIG repository achieves this goal and stands as a scalable working model for institutions to collect, track, curate, archive, and disseminate multimodal data from patients. In November 2020, a Registered Access layer was made available to the wider research community at https://cbigr-open.loris.ca, and in May 2021 fully open data will be released to complement the Registered Access data. This article outlines many of the aspects of The Neuro’s transition to Open Science by describing the data to be released, C-BIG’s full capabilities, and the design aspects that were implemented for effective data sharing.


2021 ◽  
Author(s):  
Tamara Kalandadze ◽  
Sara Ann Hart

The increasing adoption of open science practices in the last decade has been changing the scientific landscape across fields. However, developmental science has been relatively slow in adopting open science practices. To address this issue, we followed the format of Crüwell et al., (2019) and created summaries and an annotated list of informative and actionable resources discussing ten topics in developmental science: Open science; Reproducibility and replication; Open data, materials and code; Open access; Preregistration; Registered reports; Replication; Incentives; Collaborative developmental science.This article offers researchers and students in developmental science a starting point for understanding how open science intersects with developmental science. After getting familiarized with this article, the developmental scientist should understand the core tenets of open and reproducible developmental science, and feel motivated to start applying open science practices in their workflow.


2019 ◽  
Author(s):  
Rima-Maria Rahal ◽  
Johanna Havemann

Since Open Science has become a recurring buzzword for recent meta-scientific developments, this article summarizes what these developments entail. What are the reasons for discussions about Open Access, Open Data and Open Peer Review? Which technological changes can we expect and which impact will they have on society and the research community?


2021 ◽  
Author(s):  
Tony Ross-Hellauer ◽  
Stefan Reichmann ◽  
Nicki Lisa Cole ◽  
Angela Fessl ◽  
Thomas Klebel ◽  
...  

Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible, and re-usable for large audiences. However, making processes open will not per se drive wide re-use or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science’s agenda of inclusivity at risk of propagating conditions of “cumulative advantage”. With this paper, we systematically scope existing research addressing the question: “What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?” Aiming to synthesise findings, identify gaps in the literature, and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open/FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as “reproducibility” becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.


2021 ◽  
Author(s):  
Emma Norris ◽  
Isra Sulevani ◽  
Ailbhe N. Finnerty ◽  
Oscar Castro

Objectives: Concerns on the lack of reproducibility and transparency in science have led to a range of research practice reforms, broadly referred to as Open Science. The extent that physical activity interventions are embedding Open Science practices is currently unknown. In this study, we randomly sampled 100 reports of recent physical activity behaviour change interventions to estimate the prevalence of Open Science practices. Methods: One hundred reports of randomised controlled trial physical activity behaviour change interventions published between 2018-2021 were identified. Open Science practices were coded in identified reports, including: study pre-registration, protocol sharing, data-, materials- and analysis scripts-sharing, replication of a previous study, open access publication, funding sources and conflict of interest statements. Coding was performed by two independent researchers, with inter-rater reliability calculated using Krippendorffs alpha. Results: 78% of the 100 reports provided details of study pre-registration and 41% provided evidence of a published protocol. 4% provided accessible open data, 8% provided open materials and 1% provided open analysis scripts. 73% of reports were published as open access and no studies were described as replication attempts. 93% of reports declared their sources of funding and 88% provided conflicts of interest statements. A Krippendorffs alpha of 0.73 was obtained across all coding. Conclusion: Open data, materials, analysis and replication attempts are currently rare in physical activity behaviour change intervention reports, whereas funding source and conflict of interest declarations are common. Future physical activity research should increase the reproducibility of their methods and results by incorporating more Open Science practices.


2021 ◽  
Author(s):  
Kennedy Mwangi ◽  
Ben Mainye ◽  
Daniel Ouso ◽  
Esoh Kevin ◽  
Angela Muraya ◽  
...  

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing, and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20 - 50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining, and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and the challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign towards open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders, and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.


Author(s):  
Edeltraud Aspöck

Generally, open science practices are only slowly having an impact on mainstream archaeological practice. An exception is the open access to publications, which, together with open data and open methodologies may represent those practices most relevant for archaeological researchers. This article introduces a selection of archaeology projects that embrace and facilitate open science practices. Finally there will be a discussion of some of the questions and challenges the discipline is facing in its move towards an Open Archaeology.


Author(s):  
Kennedy W. Mwangi ◽  
Nyabuti Mainye ◽  
Daniel O. Ouso ◽  
Kevin Esoh ◽  
Angela W. Muraya ◽  
...  

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20–50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign toward open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.


2021 ◽  
Author(s):  
Eric R. Louderback ◽  
Sally M Gainsbury ◽  
Robert Heirene ◽  
Karen Amichia ◽  
Alessandra Grossman ◽  
...  

The replication crisis has stimulated researchers around the world to adopt open science research practices intended to reduce publication bias and improve research quality. Open science practices include study pre-registration, open data, open publication, and avoiding methods that can lead to publication bias and low replication rates. Although gambling studies uses similar research methods to behavioral research fields that have struggled with replication, we know little about the uptake of open science research practices in gambling-focused research. We conducted a scoping review of 500 recent (1/1/2016 – 12/1/2019) studies focused on gambling and problem gambling to examine the use of open science and transparent research practices. Our results showed that a small percentage of studies used most practices: whereas 54.6% (95% CI: [50.2, 58.9]) of studies used at least one of nine open science practices, each practice’s prevalence was: 1.6% for pre-registration (95% CI:[0.8, 3.1]), 3.2% for open data (95% CI:[2.0, 5.1]), 0% for open notebook, 35.2% for open access (95% CI:[31.1, 39.5]), 7.8% for open materials (95% CI:[5.8, 10.5]), 1.4% for open code (95% CI:[0.7, 2.9]), and 15.0% for preprint posting (95% CI:[12.1, 18.4]). In all, 6.4% (95% CI:[4.6, 8.9]) used a power analysis and 2.4% (95% CI:[1.4, 4.2]) of the studies were replication studies. Exploratory analyses showed that studies that used any open science practice, and open access in particular, had higher citation counts. We suggest several practical ways to enhance the uptake of open science principles and practices both within gambling studies and in science more broadly.


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