Our research activities would be better served if they were communicated in a manner that is openly accessible to the public and all researchers. The research we share is often limited to representative data included in research papers—science would be much more efficient if all reproducible research data were shared alongside detailed methods and protocols, in the paradigm called Open Science. On the other hand, one primary function of research journals is to select manuscripts of good quality, verify the authenticity of the data and its impact, and deliver to the appropriate audience for critical evaluation and verification. In the current paradigm, where publication in a subset of journals is intimately linked to research evaluation, a hypercompetitive “market” has emerged where authors compete to access a limited number of top-tier journals, leading to high rejection rates. Competition among publishers and scientific journals for market dominance resulted in an increase in both the number of journals and the cost of publishing and accessing scientific papers. Here we summarize the current problems and potential solutions from the development of AI technology discussed in the seminar at the 46th Annual Meeting of the Molecular Biology Society of Japan.

中文翻译：

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开放获取和开放科学时代的出版

如果我们的研究活动能够以公众和所有研究人员公开参与的方式进行交流，那么我们的研究活动将会得到更好的服务。我们共享的研究通常仅限于研究论文中包含的代表性数据——如果所有可重复的研究数据都与详细的方法和协议一起共享，在开放科学的范式中，科学将会更加高效。另一方面，研究期刊的一个主要功能是选择高质量的稿件，验证数据的真实性及其影响，并交付给适当的受众进行批判性评估和验证。在当前的范式中，部分期刊的发表与研究评估密切相关，因此出现了一个竞争异常激烈的“市场”，作者竞相访问有限数量的顶级期刊，从而导致很高的拒绝率。出版商和科学期刊之间争夺市场主导地位的竞争导致期刊数量以及出版和获取科学论文的成本增加。这里我们总结了第46届日本分子生物学会年会研讨会上讨论的人工智能技术发展的当前问题和潜在解决方案。