The Visual Data Analysis group at KU Leuven (part of Bioinformatics at STADIUS/ESAT, the iMinds High-Impact Initiative on Data Science, and embedded in the Data Visualization Lab) investigates how to make sense of large and/or complex datasets. In visual analytics, automated analysis techniques are combined with interactive data visualization with the aim to enable reasoning and hypothesis generation. The methodology is particularly well-fit for the discovery of unexpected phenomena in large and dynamic datasets; it is the best approach for tackling open problems for which no clear solutions seem to exist, and even the questions are unknown.
Our research focus is on visual design, interaction design, and scalability. Historically, genomics and genetics have been the principal domains that we’ve been active in, but we are also investigating applications in quantified self, health management, energy and art. For example, we investigate how to give people insight in their health data by combining data mining and visualization, and support health professionals in identifying people who require follow-up.
Check out who we are and some of the projects that we’re involved in. Much of our code is available on the vda-lab bitbucket git repository. Videos of what we create are available on the lab’s Vimeo channel.
Blog posts are contributed by all members of the group and act more as an external memory for ourselves than anything else…