Declarative Aspects in Explicative Data Mining for Computational Sensemaking

Computational sensemaking aims to develop methods and systems to "make sense" of complex data and information. The ultimate goal is then to provide insights and enhance understanding for supporting subsequent intelligent actions. Understandability and interpretability are key elements of that process as well as models and patterns captured therein. Here, declarativity helps to include guiding knowledge structures into the process, while explication provides interpretability, transparency, and explainability. This paper provides an overview of the key points and important developments in these areas, and outlines future potential and challenges.