Abstract
Publishing original scientific research is inherent to the work of a researcher. However, the pressure to maintain productivity and scientific impact can lead to research group publishing excessively, negatively affecting the mental health of a researcher. Ph.D. students and early career researchers are particularly susceptible to this pressure due to the inherent vulnerability of their positions. At present, there are no resources that concisely summarise the publication culture of a research group to help the researcher make an informed decision before joining. In this article, we present the ‘Super Researcher’ app, an R Shiny application(app) with a user-friendly interface. Using text-mining methodology to extract publicly available author data from Scopus, this pilot app has four fundamental functions to provide snapshot information that will help researchers grasp the publication culture of a research group within minutes. The ‘Super Researcher’ app provides information on: 1) institution data, 2) author’s publication, 3) co-author network plots and 4) publication journals.
The ‘Super Researcher’ app is built on R shiny which provides an interactive interface to users. This app utilizes the Big Data framework Apache Spark to mine relevant information from a huge author information database. The author’s information is stored and manipulated using both SQL(SQLite) and NoSQL(HBase) databases. Hbase is used for local data storage and manipulation while SQLite feeds data to the R Shiny interface.
In this paper, we introduce these functionalities and illustrate how this information can help guide a researcher to select a new Principle Investigator (PI) with better compatibility in terms of publication attitude using a case study. Available: https://researchmind.co.uk/super-researcher/
Competing Interest Statement
The authors have declared no competing interest.
