Chinese Sea
By Gabriel Carsenat
‘Chinese sea’ is a colorful view of the cartography of COVID-19 Scientific Literature, from the angle of nationality / country of origin or ethnicity of scientists across 30 different subject clusters.
It reflects a collaboration project of Dario Rodighiero (MIT CMS/W / Harvard Metalab), Eveline Wandl-Vogt (Ars Electronica Research Institute knowledge for humanity / Austrian Academy of Sciences), and Elian and Gabriel Carsenat (NamSor).
Using the open-source database COVID‑19 Open Research Dataset (CORD‑19) released on July 1, 2020 by the Allen Institute for AI, scientific articles are grouped by authors and analyzed with methods of Natural Language Processing.
The canvas shows the pre-eminence of Chinese names across all 30 subject clusters. Their overall share in production of science is the large blue ‘sea’ making about a third of the canvas.
Apart from China, most countries have worked in silos and focused their effort on one single subject. So their combined production of science looks like a mountainous shore.
This work was first presented at Ars Electronica 2020.