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@article{Scherngell2023,

title = {The geographical dynamics of global R&D collaboration networks in robotics: Evidence from co-patenting activities across urban areas worldwide},

author = { Thomas Scherngell and Katharina Schwegmann and Georg Zahradnik},

editor = {Celine Rozenblat from University of Lausanne SWITZERLAND},

url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0281353},

doi = {https://doi.org/10.1371/journal.pone.0281353},

year  = {2023},

date = {2023-04-13},

urldate = {2023-04-13},

journal = {PLOS ONE},

abstract = {The focus of this study is on the geography of robotics Research and Development (R&D) activities. The objectives are, first, to identify hotspots in robotics R&D worldwide, and second, to characterise structures and dynamics of global robotics R&D collaboration networks through detailed geographical lenses of global urban areas. We use patents as marker for R&D activities, and accordingly focus on technologically oriented R&D, drawing on information from patents applied for between 2002 and 2016. We employ an appropriate search strategy to identify relevant robotics patents based on detailed levels of the Cooperative Patent Classification (CPC) and assign patents to more than 900 global urban areas based on the inventor addresses. The co-patent networks are examined from a Social Network Analysis (SNA) perspective by means of robotics co-patents, contributing to a global network where urban areas are the nodes inter-linked by joint inventive activities recorded in robotics patents. Global SNA measures illustrate structures and dynamics of the network as a whole, while local measures indicate the specific positioning and roles of urban areas in the network. The results are original in characterising the global spatial emergence of this generic new industry, highlighting prominent urban hotspots in terms of specialisation in robotics R&D, pointing to a global shift reflected by the increasing role of emerging economies, in particular China. The global robotics R&D has grown significantly both in total patenting and also in terms of R&D collaboration activities between urban areas. Also, for the networks, growth is not equally distributed, but is rather characterised by significant spatial shifts, both in terms of cities declining or climbing up the specialisation ranking, but even more in terms of the spatial network structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Testoni2021,

title = {Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda},

author = {Federico E. Testoni and Mercedes García Carrillo and Marc-André Gagnon and Cecilia Rikap and Matías Blaustein

},

editor = {Quinn Grundy},

url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249661},

doi = { https://doi.org/10.1371/journal.pone.0249661},

year  = {2021},

date = {2021-04-07},

urldate = {2021-04-07},

journal = {PLoS ONE},

abstract = {Conflicts of interest in biomedical research can influence research results and drive research agendas away from public health priorities. Previous agenda-setting studies share two shortfalls: they only account for direct connections between academic institutions and firms, as well as potential bias based on researchers’ personal beliefs. This paper’s goal is to determine the key actors and contents of the prevailing health and biomedical sciences (HBMS) research agenda, overcoming these shortfalls.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{raimbault2016mapping,

title = {Mapping the emergence of synthetic biology},

author = {Benjamin Raimbault and Jean-Philippe Cointet and Pierre-Benoît Joly},

url = {https://doi.org/10.1371/journal.pone.0161522},

doi = {10.1371/journal.pone.0161522},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

journal = {PloS one},

volume = {11},

number = {9},

pages = {e0161522},

publisher = {Public Library of Science},

abstract = {In this paper, we apply an original scientometric analyses to a corpus comprising synthetic biology (SynBio) publications in Thomson Reuters Web of Science to characterize the emergence of this new scientific field. Three results were drawn from this empirical investigation. First, despite the exponential growth of publications, the study of population level statistics (newcomers proportion, collaboration network structure) shows that SynBio has entered a stabilization process since 2010. Second, the mapping of textual and citational networks shows that SynBio is characterized by high heterogeneity and four different approaches: the central approach, where biobrick engineering is the most widespread; genome engineering; protocell creation; and metabolic engineering. We suggest that synthetic biology acts as an umbrella term allowing for the mobilization of resources, and also serves to relate scientific content and promises of applications. Third, we observed a strong intertwinement between epistemic and socio-economic dynamics. Measuring scientific production and impact and using structural analysis data, we identified a core set of mostly American scientists. Biographical analysis shows that these central and influential scientists act as “boundary spanners,” meaning that their importance to the field lies not only in their academic contributions, but also in their capacity to interact with other social spaces that are outside the academic sphere.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chavalarias2013phylomemetic,

title = {Phylomemetic patterns in science evolution - the rise and fall of scientific fields},

author = {David Chavalarias and Jean-Philippe Cointet},

url = {https://doi.org/10.1371/journal.pone.0054847},

doi = {10.1371/journal.pone.0054847},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {PloS one},

volume = {8},

number = {2},

pages = {e54847},

publisher = {Public Library of Science},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}