Mapping the Evolution of Scientific Fields

Abstract

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985–2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

How are topics born? Understanding the research dynamics preceding the emergence of new areas

“…Firstly, they appear to support our hypothesis about the existence of an embryonic phase in the lifecycle of research topics. Secondly, they bring new empirical evidence to fundamental theories in Philosophy of Science, which are concerned with the evolution of scientific disciplines, e.g., Herrera, Roberts & Gulbahce (2010), Kuhn (2012), Nowotny, Scott &Gibbons (2013), andSun et al (2013). Finally, they highlight that new topics tend to be born in an environment in which previously less interconnected research areas start to cross-fertilise and generate new ideas.…”

“…In this context, Becher & Trowler (2001) explained that, even if science proceeds towards more specific disciplines, and thus researchers in different communities become less compatible, they are still inclined to collaborate for mutual benefit. Herrera, Roberts & Gulbahce (2010), Sun et al (2013) and Nowotny, Scott & Gibbons (2013) suggested that the development of new topics is encouraged by the crossfertilisation of established research areas and recognised that multidisciplinary approaches foster new developments and innovative thinking. Sun et al (2013) and Osborne, Scavo & Motta (2014) provided empirical evidence to these theories by analysing the social dynamics of researchers and their effects on the formation and life-cycle of research communities and topics.…”

Community structure of the physical review citation network

“…While anecdotal information exists about the identity and evolution of some of the more prominent subfields of physics (Capri, 2007), here we determine their quantitative properties, such as their size, time history, and citation impact. A related work recently studied the evolution of scientific fields through the PACS (Physics and Astronomy Classification Scheme) numbers of each article (Herrera et al, 2009).…”

“…While these methods sometimes work reasonably well, they can fail to identify communities when applied to networks that lie outside of the domain of their immediate application . More recent work has led to the formulation of new and powerful methods to detect communities in complex networks, both with undirected (Herrera et al, 2009;Kim, Son, & Jeong 2009;Lancichinetti, Fortunato, & Kertesz, 2009;Leicht & Newman, 2008;Porter et al, 2010;Rosvall & Bergstrom, 2008) and directed (Leicht & Newman, 2008) links. A systematic review of these developments is given in (Porter et al, 2010).…”

On the Value of Portfolio Diversity in Heart, Lung, and Blood Research

“…1 Other authors have cited examples supporting the importance of diversity in science: multidisciplinary interactions have repeatedly been shown to generate greater degrees of rigor, creativity, evolution of ideas, academic productivity, 4 and innovation. 5,6 Page argues that when faced with difficult problems, different people (or more generally different agents) can bring different "toolboxes." Diverse toolboxes offer varying perspectives, interpretations, heuristics, and prediction models.…”