On Wednesday, December 2nd, MRC Visiting Scholar Kedma Duarte presented a talk on her research, titled “Assessing Researcher’s Collaborative Quality.” Kedma is a PhD Student in the Engineering and Management Knowledge Graduate Program of Engineering and Management Knowledge at the Federal University of Santa Catarina, Florianopolis, SC, Brazil.
Abstract: Funding agencies and hiring and promotion committees are frequently tasked to select the best researchers. Recently, due to the increased demand for collaborative projects, they need to select the best researchers for collaboration. The literature however does not provide the science or methodologies to identify collaborative quality.
The overarching research questions in my work are:
- What is collaborative quality in research?
- What are the attributes that distinguish quality in research collaborators?
Answering these questions will enable the development of a methodology to measure collaborative quality, which would allow us to rank research collaborators, and mentor researchers to become better collaborators. The focus is thus on individual researchers – the collaborators, and not on collaborations. We started by reviewing the research collaboration literature seeking attributes that have already been used to characterize research collaborators. Currently, we are investigating machine learning methods to identify predictive attributes of research collaborators. For experiments, we will use the Brazilian database Lattes to explore the characteristics of research collaborators. Lattes platform is a database of curriculum vitae (CV), with more than 3 million profiles of researchers.