Computer analysis is now an essential part of science.
It is often said that the difference between science and superstition is that science is reproducible. Unfortunately, this is not the case with many scientific papers, which makes them as credible as fables. p>
Since the mid-17th century, the output of a typical scientific study has been an article-style journal describing the findings. But today, in fields ranging from astronomy to microbiology, much of the technical work of a journal article involves writing code to process the data set. If data and code are not available, researchers will no longer be able to reproduce the work of the original authors, and most importantly, they may not be able to build on the work to discover new methods and discoveries.
Thanks to cultural change and financial needs, more researchers are preparing to open data and open source. Even journals that are 100 years old, such as the Economics Quarterly or the Journal of the Royal Statistical Society, now require authors to submit duplicate material — including data and code — with nearly every article. Some researchers welcome the new paradigm and see the value of advancing science through deeper collaboration. But others feel the burden of learning to use distribution-related tools like Git, Docker, Jupyter, and other less important words. The Make Data Count researcher describes the ideals that these data sharing requirements aspire to. "We want a world where data is used routinely for discovery, for the advancement of science, and for evidence- and data-based policy," he said. In some places, this is the future. "There are data sets that drive the whole field," he says. For example, he cites this data set of 16,468 tree densities that have been downloaded more than 17,000 times. p>
With this model in mind, journal editors are increasingly publishing data and the subject matter is open source. . I reviewed about 2,700 journals published by Springer, one of the largest academic journal publishers, for submission guidelines that state that authors must have access to all content such as data and symbols. p> Advertising
Results are open source and custom code data appear in some areas more than others. Among environmental journals, 37% require availability, while only 7% require surgical journals and 6% require educational journals. Among these other disciplines, 16 to 19 percent of the journals in management, engineering, physics, economics, general medicine, and psychology express this requirement. p> LoadingBen Klemens
These participation requirements are often based on the "available on demand" standard. From 2017 to 2019, Tsuyoshi Miakawa, editor of Molecular Brain, responded to 41 posts and asked the authors to provide the full source information for the review. According to the magazine, only one author has done so.
Science has a policy that data and content such as code should be available Of the 204 selected articles from the journal, Stodden's team managed 89 articles, with 115 requests for non-response, broken promises, fruitless redirects, or sometimes aggressive rejections. p>
Building on his efforts to replicate the work of other statisticians, Thomas Lumley, professor of biostatistics at the University of Auckland in New Zealand said, "When people put it in their articles, they usually mean 'data not available'." As a result, there are a number of A growing number of investors and journals.Researchers now have a formal plan to publish their data.
The National Institutes of Health (NIH) provided more than $30 billion in competitive research funding in 2020 for each grant application. With the data component it must include data management and sharing software. Applicants are encouraged to deposit their work in existing repositories, such as the NIH Genotype and Phenotype Database (dbGap). If you prefer some of the multi-billion dollar annual grants offered by the National Science Foundation, you also need a data management software. p>
Maintain repeatable science in a world of custom code and data
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