Authors: Matteo Golfarelli, Stefano Rizzi, Tommaso Pirini
Tags: 2017, conceptual modeling
The H2020 TOREADOR Project adopts a model-driven architecture to streamline big data analytics and make it widely available to companies as a service. Our work in this context focuses on visualization, in particular on how to automate the translation of the visualization objectives declared by the user into a suitable visualization type. To this end we first define a visualization context based on seven prioritizable coordinates for assessing the user’s objectives and describing the data to be visualized; then we propose a skyline-based technique for automatically translating a visualization context into a set of suitable visualization types. Finally, we evaluate our approach on a real use case excerpted from the pilot applications of TOREADOR.Read the full paper here: https://link-springer-com.proxy2.hec.ca/chapter/10.1007/978-3-319-70625-2_5
