Is Science subjected to laws of evolution as living species are? Are there patterns in science history ? Until recently, tackling these questions with large-scale empirical protocols was hardly possible. The ever-growing availability of data about scientific publications combined with progresses in scientific fields dynamics modeling now makes it possible to envision that these questions shall soon be answered.
As a first step, David Chavalarias and Jean-Philippe Cointet have developped a method to automatically reconstruct representations of science evolution from the large scale analysis of digital repositories : « phylomemies ». A phylomemy, by analogy with phylogenies in biology, describes the transformations of scientific fields over time: from most simple events like field emergence or decline, to more complex transformation like field merging or splitting. This poster presents, for the first time, a still partial representation of a phylomemy, related to Future and Emerging Technologies, built from the analysis of tens of millons of scientific paper metadata.
Phylomemies can also be used as high level descriptions of science evolution that, once interfaced with digital libraries, offer new ways to browse the large datasets of documents.
We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns. Some structural properties of the scientific fields – in particular their density -, which are defined independently of the phylomemy reconstruction, are clearly correlated with their status and their fate in the phylomemy (like their age or their short term survival). Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.
Chavalarias, David, and Jean-Philippe Cointet (2013) Phylomemetic Patterns in Science Evolution: The Rise and Fall of Scientific Fields. PLoS ONE 8:2.
This map is part of the Places and Spaces Exhibition 2013.