학술논문

Training the Next Generation of Doctoral Researchers in Data Science: The Impact on Publications and Beyond
Document Type
Periodical
Source
IEEE Transactions on Technology and Society IEEE Trans. Technol. Soc. Technology and Society, IEEE Transactions on. 4(3):241-247 Sep, 2023
Subject
Engineering Profession
General Topics for Engineers
Data science
Training
Engineering profession
Social sciences
Business
Collaboration
Computational modeling
Career development
Scientific publishing
Computational data science
doctoral training
publishing
academic careers
Language
ISSN
2637-6415
Abstract
Developments in data science methods have changed how we design, review and publish social science research. The impact on academic development has been multifaceted: new research opportunities have come with additional demands on training researchers to develop advanced data skills and apply them to research outputs. For early career researchers, meeting existing work demands and investing time in data skills can be a difficult proposition. In this paper, we consider the challenges that doctoral and early career researchers face when it comes to short- and long-term career goals and discuss how to collectively overcome them. Recommendations are organised around the key areas identified by the Learning, Leading, Linking framework. We emphasise that doctoral researchers in social sciences should be supported to develop their skills and pursue meaningful collaborations with other disciplines and external stakeholders as domain specialists.