On Knowledge Discovery and interactive intelligent Visualization of biomedical data: Challenges in Human–Computer Interaction & Biomedical Informatics

Biomedical Informatics can be defined as “the interdisciplinary field that studies and pursues the effective use of biomedical data, information and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health.” However, professionals in the life sciences are facing an increasing quantity of highly complex, multi-dimensional and weakly structured data. While researchers in Human-Computer Interaction (HCI) and Knowledge Discovery in Databases (KDD) have for long been working independently to develop methods that can support expert end users to identify, extract and understand information out of this data, it is obvious that an interdisciplinary approach to bring these two fields closer together can yield synergies in the application of these methods to weakly structured complex medical data sets. The aim is to support end users to learn how to interactively analyse information properties and to visualize the most relevant parts – in order to gain knowledge, and finally wisdom, to support a smarter decision making. The danger is not only to get overwhelmed by increasing masses of data, moreover, there is the risk of modelling artifacts.