Data science publication: Thirty-six years lesson of scientometric review
| Keyword | Data science; Publication mapping; Scientometric; Vosviewer |
| Authors | Purnomo A., Rosyidah E., Firdaus M., Asitah N., Septianto A. |
| agung.purnomo@binus.ac.id | |
| Published Year | 2020 |
Abstract
Data science as part of technological development is growing and needed. It has been
research yet the notion about data science review publication which showed the big picture
using data from all countries. This research aims to study the position of the international
publication map of data science indexed by Scopus using scientometric review. Scientometric
methods and analyzed research data was used to analyze search results service from Scopus
and the VOSviewer application. The research data of 5, 202 documents published from 1983
to 2019 were obtained from the Scopus database. Most countries, subject areas, and type
documents in data science publications were the United States, computer science; and
conference paper. There were ten collaborative researchers’ group patterns. This research
proposes a convergence axis classification consisting of data science publication to
characterize the body of knowledge generated from three decades of publication: Machine
learning, Organism, Data mining, and Data analysis, abbreviated as MODD themes. © 2020
IEEE.