Panos Vassiliadis, Veronika Peralta, Patrick Marcel, Dimos Gkitsakis, Angeliki Dougia, Faten El Outa
We introduce a conceptual model for highlights to support automated data analysis and storytelling. Highlights reveal key facts, of high significance, that are hidden in the data with which a data analyst works. The model builds on the concepts of Holistic and Elementary Highlights, along with their context, constituents and interrelationships, whose synergy can identify internal properties, patterns and key facts in a dataset being analyzed. We also report how the related literature fits within the model, as well as a first implementation of it.
Panos Vassiliadis, Veronika Peralta, Patrick Marcel, Dimos Gkitsakis, Angeliki Dougia, Faten El Outa. A Conceptual Model for Data Analysis Highlights.
Companion Proceedings of the 44th International Conference on Conceptual Modeling (ER 2025): ER Forum, Poitiers, France, 20-23 October 2025.
[ Local copy of the paper (PDF)]
More details at: [my page on a paradigm shift for OLAP]