Rexplore leverages novel solutions in large-scale data mining, semantic technologies and visual analytics, to

provide an innovative environment for exploring and making sense of scholarly data. In particular, Rexplore allows users:

• To detect and make sense of important trends in research, such as, significant migrations of researchers from one area to another, the emergence of new topics, the evolution of communities within a particular area, and several others.

• To identify a variety of interesting relations between researchers, e.g., recognizing authors who share similar research trajectories. These relations go well beyond the standard co-authorship links or relationships informed by social networks, which are commonly found in other systems.

• To perform fine-grained expert search with respect to detailed multi-dimensional parameters.

In this seminar I will provide an overview of Rexplore and in particular I will illustrate some of its key innovative elements of the tool, including:

• Metrics and visualizations conceived to assess similarities between authors, migration flows and the performance of an author in different topics.

• Klink, an algorithm to automatically craft semantic relationships between research areas from keywords associated to documents and external sources.

• A novel approach to building science maps, enabling them to describe the diachronic behavior of research communities, how they interact and how they react to external events.