Ventocilla, Elio AlejandroMartins, Rafael M.Paulovich, Fernando V.Riveiro, MariaArchambault, Daniel and Nabney, Ian and Peltonen, Jaakko2020-05-242020-05-242020978-3-03868-113-7https://doi.org/10.2312/mlvis.20201099https://diglib.eg.org:443/handle/10.2312/mlvis20201099As large datasets become more common, so becomes the necessity for exploratory approaches that allow iterative, trial-anderror analysis. Without such solutions, hypothesis testing and exploratory data analysis may become cumbersome due to long waiting times for feedback from computationally-intensive algorithms. This work presents a process model for progressive multidimensional projections (P-MDPs) that enables early feedback and user involvement in the process, complementing previous work by providing a lower level of abstraction and describing the specific elements that can be used to provide early system feedback, and those which can be enabled for user interaction. Additionally, we outline a set of design constraints that must be taken into account to ensure the usability of a solution regarding feedback time, visual cluttering, and the interactivity of the view. To address these constraints, we propose the use of incremental vector quantization (iVQ) as a core step within the process. To illustrate the feasibility of the model, and the usefulness of the proposed iVQ-based solution, we present a prototype that demonstrates how the different usability constraints can be accounted for, regardless of the size of a dataset.Human centered computingVisual analytics10.2312/mlvis.202010991-5