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Open Science, Reproducible Research, Findable, Accessible, Interoperable and Reusable (FAIR) data principles are long term goals for scientific dissemination. However, the implementation of these principles calls for a reinspection of our means of dissemination. In our viewpoint, we discuss and advocate, in the context of nonlinear science, how a notebook article represents an essential step toward this objective by fully embracing cloud computing solutions. Notebook articles as scholar articles offer an alternative, efficient and more ethical way to disseminate research through their versatile environment. This format invites the readers to delve deeper into the reported research. Through the interactivity of the notebook articles, research results such as for instance equations and figures are reproducible even for non-expert readers. The codes and methods are available, in a transparent manner, to interested readers. The methods can be reused and adapted to answer additional questions in related topics. The codes run on cloud computing services, which provide easy access, even to low-income countries and research groups. The versatility of this environment provides the stakeholders - from the researchers to the publishers - with opportunities to disseminate the research results in innovative ways.
Research on the construction of traditional information science methodology taxonomy is mostly conducted manually. From the limited corpus, researchers have attempted to summarize some of the research methodology entities into several abstract levels
Developers in data science and other domains frequently use computational notebooks to create exploratory analyses and prototype models. However, they often struggle to incorporate existing software engineering tooling into these notebook-based workf
Questionable publications have been accused of greedy practices; however, their influence on academia has not been gauged. Here, we probe the impact of questionable publications through a systematic and comprehensive analysis with various participant
In this article, we analyze the citations to articles published in 11 biological and medical journals from 2003 to 2007 that employ author-choice open access models. Controlling for known explanatory predictors of citations, only 2 of the 11 journals
We present the results of a large-scale study of potentially predatory journals (PPJ) represented in the Scopus database, which is widely used for research evaluation. Both journal metrics and country, disciplinary data have been evaluated for differ