论文标题
生物医学创新的演变通过数十亿个不同的文章级网格关键字组合量化
Evolution of biomedical innovation quantified via billions of distinct article-level MeSH keyword combinations
论文作者
论文摘要
我们开发了一种系统的方法来基于医学主题标题(网格)的全面本体学本生物医学科学中的组合创新。这种方法利用了一个专家定义的知识本体,该知识本体具有广度(从1902年开始,PubMed索引的2500万篇文章分析了27,875个网格)和深度(我们在主要的网格术语中区分了主要的和次要的网格术语,以确定仅根据主要研究主题构建的知识网络表示的差异)。通过这种统一的分辨率,我们区分了三种不同的创新模式,从而有助于组合知识网络:(i)与新概念和实体的出现相关的概念创新(以新网格的进入衡量); (ii)重组创新,与新组合的出现有关,本身包括两种类型:外围(即涉及新知识的组合)和核心(仅由预先存在的知识组成)。我们寻求解决的另一个相关问题是,除了更传统的二元或成对组合外,还要研究三胞胎和四重奏组合,还提供了与高阶组合相关的任何新现象的证据。对组合创新产量结果的大小,生长和覆盖率的分析在很大程度上与组合顺序无关,从而表明常见的二元方法足以捕获基本现象。我们的主要结果是双重的。 (b)概念创新越来越集中在单一研究文章中,这是最近向融合科学转变的范式的预兆。
We develop a systematic approach to measuring combinatorial innovation in the biomedical sciences based upon the comprehensive ontology of Medical Subject Headings (MeSH). This approach leverages an expert-defined knowledge ontology that features both breadth (27,875 MeSH analyzed across 25 million articles indexed by PubMed from 1902 onwards) and depth (we differentiate between Major and Minor MeSH terms to identify differences in the knowledge network representation constructed from primary research topics only). With this level of uniform resolution we differentiate between three different modes of innovation contributing to the combinatorial knowledge network: (i) conceptual innovation associated with the emergence of new concepts and entities (measured as the entry of new MeSH); and (ii) recombinant innovation, associated with the emergence of new combinations, which itself consists of two types: peripheral (i.e., combinations involving new knowledge) and core (combinations comprised of pre-existing knowledge only). Another relevant question we seek to address is whether examining triplet and quartet combinations, in addition to the more traditional dyadic or pairwise combinations, provide evidence of any new phenomena associated with higher-order combinations. Analysis of the size, growth, and coverage of combinatorial innovation yield results that are largely independent of the combination order, thereby suggesting that the common dyadic approach is sufficient to capture essential phenomena. Our main results are twofold: (a) despite the persistent addition of new MeSH terms, the network is densifying over time meaning that scholars are increasingly exploring and realizing the vast space of all knowledge combinations; and (b) conceptual innovation is increasingly concentrated within single research articles, a harbinger of the recent paradigm shift towards convergence science.