Welcome to the Interactive Visual Data Analysis Group
The Interactive Visual Data Analysis Group is lead by Prof. Jürgen Bernard.
Our primary research focus is at the intersection between Information Visualization, Visual Analytics, Human-Computer Interaction, and Machine Learning. Our projects follow a human-centered approach to data science, in order to foster the involvement of humans in the data analysis process with interactive visual interfaces. Our research is on the combination of the strength of humans and machines in an iterative and incremental data analysis process in order to tackle remaining data science challenges.
Our research addresses three different challenge areas.
Data-oriented challenges arise from different types of complexity data comes with. Examples are heterogeneous data, dirty data, uncertain data, or unlabeled data.
Model-oriented challenges refer to the need for an effective and efficient use of algorithmic models to cope with data challenges. Often, several models are included in a data analysis process. Example challenges include data preprocessing, model building, model quality assessment, or model explanation.
User-oriented challenges refer to human aspects in data analysis and are particularly interesting for the research focus of IVDA. User-oriented challenges are different degrees of user expertise, users’ personalization intents, understanding and supporting user preferences with respect to data and tasks, as well as human factors in a broader sense.
Human-Centered Data Science
Our contributions refer to human-centered data science solutions, tailored to the information need of individual users. These new approaches will also make machine learning applicable to larger user groups in the context of data science and digitalization initiatives.