Case-Based Comparison of Career Trajectories

Data generated across time may not be easily comparable in its original form thus potentially leading to results that may be perceived as unfair to some. We investigate quality assessment of scholarly researchers from their curricula vitae (CVs) for processes such as hiring, promotion, and grant funding. In previous work, we demonstrated that case-based reasoning (CBR) offers advantages as a transparent methodology to assess researcher quality. Its benefits include consistency, transparency, ability to adapt to specific purposes, and ability to provide explanation. The problem we now face is how to preprocess the data from the CVs to compare researchers whose scholarly production is achieved under different conditions, different points in time, and span different career trajectory lengths. We propose strategies to deal with these aspects of time during preprocessing of the data for case representation. We use 1,000 CVs from the Brazilian Lattes database to illustrate.