The Impact of Conceptual Modeling on Dataset Completeness: A Field Experiment

This paper investigates the impact of conceptual modeling on the information completeness dimension of information quality in the context of user-generated content. We propose a theoretical relationship between conceptual modeling approaches and information completeness and hypothesize that traditional classbased conceptual modeling negatively affects information completeness. We conducted a field experiment in the context of citizen science in biology. The empirical evidence demonstrates that users assigned to an instantiation that is based on class-based conceptual modeling provide fewer observations than users assigned to an instance-based condition. Users in the instance-based condition also provided a greater number of new classes of organisms. The findings support the proposed hypotheses and establish that conceptual modeling is an important factor in evaluating and increasing information completeness in user-generated content.