Growth of science is a prevalent issue in science of science studies. In recent years, two new bibliographic databases have been introduced which can be used to study growth processes in science from centuries back: Dimensions from Digital Science and Microsoft Academic. In this study, we used publication data from these new databases and added publication data from two established databases (Web of Science from Clarivate Analytics and Scopus from Elsevier) to investigate scientific growth processes from the beginning of the modern science system until today. We estimated regression models that included simultaneously the publication counts from the four databases. The results of the unrestricted growth of science calculations show that the overall growth rate amounts to 4.02% with a doubling time of 16.8 years. As the comparison of various segmented regression models in the current study revealed, the model with five segments fits the publication data best. We demonstrated that these segments with different growth rates can be interpreted very well, since they are related to either phases of economic (e.g., industrialization) and / or political developments (e.g., Second World War). In this study, we additionally analyzed scientific growth in two broad fields and the relationship of scientific and economic growth in UK. We focused on this country, since long-time series for publication counts and economic growth indices were available.
翻译:科学增长是科学研究科学的一个普遍问题。近些年来,引入了两个新的书目数据库,可以用来研究几个世纪前的科学增长过程:数字科学和微软学术的层面。在本研究中,我们使用这些新数据库的出版数据,并从两个已建立的数据库(Clarivate Analytics科学网和Elsevier的Scopus科学网)增加出版物数据,以调查从现代科学系统开始到今天的科学增长过程。我们估计了包括四个数据库出版数字的回归模型。科学无限制增长的结果表明,总体增长率达到4.02 %, 翻了一番,16.8年。通过对目前研究中各种分层回归模型的比较,该模型与五个部分的出版数据最相匹配。我们证明,这些具有不同增长率的部分可以很好地解释,因为它们与经济(例如工业化)和/或政治发展(例如第二次世界大战)两个阶段有关。在这项研究中,我们进一步分析了两个广泛的科学增长领域的科学增长和经济增长指数,自英国以来的这一时期以来,我们着重分析了科学增长和经济增长指数的系列。