scholarly journals The C-BIG Repository: an Institution-Level Open Science Platform

2021 ◽  
Author(s):  
Samir Das ◽  
Rida Abou-Haidar ◽  
Henri Rabalais ◽  
Sonia Denise Lai Wing Sun ◽  
Zaliqa Rosli ◽  
...  
Keyword(s):  
Neurological Diseases ◽  
Open Data ◽  
Open Science ◽  
Data Repository ◽  
Multiple Stakeholders ◽  
Montreal Neurological Institute ◽  
Multimodal Data ◽  
Small Patient ◽  
Clinical Data Repository ◽  
Access Data

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.

scholarly journals Born-Open Data for E-Prime

2020 ◽  
Author(s):  
Denis Cousineau
Keyword(s):  
Open Access ◽  
Open Data ◽  
Open Science ◽  
Research Community ◽  
Data Repository ◽  
Data Frame ◽  
Science Practices ◽  
Data Practices ◽  
Data Files ◽  
Access Data

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.

scholarly journals Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing

Metabolomics ◽  
2019 ◽  
Vol 15 (10) ◽  
Author(s):  
Kevin M. Mendez ◽  
Leighton Pritchard ◽  
Stacey N. Reinke ◽  
David I. Broadhurst
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Data Science ◽  
Open Data ◽  
Open Science ◽  
Data Repository ◽  
Data Repositories ◽  
Fully Integrated ◽  
Computing Platform ◽  
Novices And Experts

Abstract Background A lack of transparency and reporting standards in the scientific community has led to increasing and widespread concerns relating to reproduction and integrity of results. As an omics science, which generates vast amounts of data and relies heavily on data science for deriving biological meaning, metabolomics is highly vulnerable to irreproducibility. The metabolomics community has made substantial efforts to align with FAIR data standards by promoting open data formats, data repositories, online spectral libraries, and metabolite databases. Open data analysis platforms also exist; however, they tend to be inflexible and rely on the user to adequately report their methods and results. To enable FAIR data science in metabolomics, methods and results need to be transparently disseminated in a manner that is rapid, reusable, and fully integrated with the published work. To ensure broad use within the community such a framework also needs to be inclusive and intuitive for both computational novices and experts alike. Aim of Review To encourage metabolomics researchers from all backgrounds to take control of their own data science, mould it to their personal requirements, and enthusiastically share resources through open science. Key Scientific Concepts of Review This tutorial introduces the concept of interactive web-based computational laboratory notebooks. The reader is guided through a set of experiential tutorials specifically targeted at metabolomics researchers, based around the Jupyter Notebook web application, GitHub data repository, and Binder cloud computing platform.

scholarly journals Research Data Management Implementation at Peking University Library: Foster and Promote Open Science and Open Data

2021 ◽  
Vol 3 (1) ◽  
pp. 189-204
Author(s):  
Hua Nie ◽  
Pengcheng Luo ◽  
Ping Fu
Keyword(s):  
Data Management ◽  
Open Data ◽  
Implementation Process ◽  
Open Science ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management ◽  
University Library ◽  
Open Research ◽  
Peking University

Research Data Management (RDM) has become increasingly important for more and more academic institutions. Using the Peking University Open Research Data Repository (PKU-ORDR) project as an example, this paper will review a library-based university-wide open research data repository project and related RDM services implementation process including project kickoff, needs assessment, partnerships establishment, software investigation and selection, software customization, as well as data curation services and training. Through the review, some issues revealed during the stages of the implementation process are also discussed and addressed in the paper such as awareness of research data, demands from data providers and users, data policies and requirements from home institution, requirements from funding agencies and publishers, the collaboration between administrative units and libraries, and concerns from data providers and users. The significance of the study is that the paper shows an example of creating an Open Data repository and RDM services for other Chinese academic libraries planning to implement their RDM services for their home institutions. The authors of the paper have also observed since the PKU-ORDR and RDM services implemented in 2015, the Peking University Library (PKUL) has helped numerous researchers to support the entire research life cycle and enhanced Open Science (OS) practices on campus, as well as impacted the national OS movement in China through various national events and activities hosted by the PKUL.

scholarly journals The impact of the National Heart, Lung, and Blood Institute data: analyzing published articles that used BioLINCC open access data

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 30
Author(s):  
Saif Aldeen AlRyalat ◽  
Osama El Khatib ◽  
Ola Al-qawasmi ◽  
Hadeel Alkasrawi ◽  
Raneem al Zu’bi ◽  
...  
Keyword(s):  
Open Data ◽  
Data Repository ◽  
Blood Institute ◽  
National Heart Lung ◽  
Pubmed Search ◽  
Number Of Publications ◽  
Almost All ◽  
Number Of Citations ◽  
The Impact ◽  
Access Data

Background: Data sharing is now a mandatory prerequisite for several major funders and journals, where researchers are obligated to deposit the data resulting from their studies in an openly accessible repository. Biomedical open data are now widely available in almost all disciplines, where researchers can freely access and reuse these data in new studies. We aim to assess the impact of open data in terms of publications generated using open data and citations received by these publications, where we will analyze publications that used the Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) as an example. Methods: As of July 2019, there was a total of 194 datasets stored in BioLINCC repository and accessable through their portal. We requested the full list of publications that used these datasets from BioLINCC, and we also performed a supplementary PubMed search for other publications. We used Web of Science (WoS) to analyze the characteristics of publications and the citations they received. Results: 1,086 published articles used data from BioLINCC repository, but only 987 (90.88%) articles were WoS indexed. The number of publications has steadily increased since 2002 and peaked in 2018 with a total number of 138 publications on that year. The 987 open data publications received a total of 34,181 citations up to 1st October 2019. The average citation per item for the open data publications was 34.63. The total number of citations received by open data publications per year has increased from only 2 citations in 2002, peaking in 2018 with 2361 citations. Conclusion: The vast majority of studies that used BioLINCC open data were published in WoS indexed journals and are receiving an increasing number of citations.

scholarly journals Total SciComm: A Strategy for Communicating Open Science

Publications ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 31
Author(s):  
Manh-Toan Ho ◽  
Manh-Tung Ho ◽  
Quan-Hoang Vuong
Keyword(s):  
Social Media ◽  
Science Communication ◽  
Scientific Community ◽  
Open Data ◽  
Open Science ◽  
Central Idea ◽  
Retracted Article ◽  
Scientific Ideas

This paper seeks to introduce a strategy of science communication: Total SciComm or all-out science communication. We proposed that to maximize the outreach and impact, scientists should use different media to communicate different aspects of science, from core ideas to methods. The paper uses an example of a debate surrounding a now-retracted article in the Nature journal, in which open data, preprints, social media, and blogs are being used for a meaningful scientific conversation. The case embodied the central idea of Total SciComm: the scientific community employs every medium to communicate scientific ideas and engages all scientists in the process.

scholarly journals Learning Open Science by doing Open Science. A reflection of a qualitative research project-based seminar

2020 ◽  
Vol 36 (3) ◽  
pp. 263-279
Author(s):  
Isabel Steinhardt
Keyword(s):  
Qualitative Research ◽  
Open Source ◽  
Knowledge Society ◽  
Open Data ◽  
Open Science ◽  
Research Project ◽  
Science Practices ◽  
Bachelor's Degrees ◽  
Participatory Technologies ◽  
Digital Knowledge

Openness in science and education is increasing in importance within the digital knowledge society. So far, less attention has been paid to teaching Open Science in bachelor’s degrees or in qualitative methods. Therefore, the aim of this article is to use a seminar example to explore what Open Science practices can be taught in qualitative research and how digital tools can be involved. The seminar focused on the following practices: Open data practices, the practice of using the free and open source tool “Collaborative online Interpretation, the practice of participating, cooperating, collaborating and contributing through participatory technologies and in social (based) networks. To learn Open Science practices, the students were involved in a qualitative research project about “Use of digital technologies for the study and habitus of students”. The study shows the practices of Open Data are easy to teach, whereas the use of free and open source tools and participatory technologies for collaboration, participation, cooperation and contribution is more difficult. In addition, a cultural shift would have to take place within German universities to promote Open Science practices in general.

scholarly journals An open toolkit for tracking open science partnership implementation and impact

2019 ◽  
Vol 3 ◽  
pp. 1442 ◽  
Author(s):  
E. Richard Gold ◽  
Sarah E. Ali-Khan ◽  
Liz Allen ◽  
Lluis Ballell ◽  
Manoel Barral-Netto ◽  
...  
Keyword(s):  
Annual Report ◽  
Open Data ◽  
Structured Interview ◽  
Open Science ◽  
Social Scientists ◽  
Policy Makers ◽  
Ethical Concerns ◽  
Research And Innovation ◽  
Survey Form ◽  
The Impact

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects.

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