Conceptual Data Model For Research Collaborators
We review the literature in search for attributes to characterize scholarly researchers, with a particular focus on collaborative work given its vast relevance and ubiquity. Our ultimate goal is to conduct studies to inform research related decisions, primarily focusing on researcher quality assessment. Recent efforts to design and maintain high-quality curriculum vitae (CV) databases, also called profiling systems, make them a valuable resource in data analyses to support advancements in science and technology. This paper is concerned with the use of CV data, particularly to enhance our understanding of the fields in CV databases, which tend to vary along different local contexts. Our contribution is a conceptual data model to assess researcher quality that aligns with the literature and accommodates collaboration-related concepts. Although we set out to investigate attributes for a data model with emphasis on research collaborators, our studies revealed that the model is independent of any particular emphasis. Any purpose or emphasis required to assess researcher quality should utilize the values of the attributes because they are the ones that reflect quality. Our studies also revealed that some dimensions of a researcher context entail meta-dimensions. For example, under the accomplishment dimension, every valued attribute (e.g., funded proposal) entails a process to deliver it that may derive more attributes
(e.g., proposal written in collaboration with others) making processes a meta-dimension. This conceptual model of researcher’s metadata can be used as the basis to select fields to be used in data and reasoning studies that rely on CV databases.