To this day, data-driven science is a widely accepted concept in the digital library (DL) context (Hey et al. in The fourth paradigm: data-intensive scientific discovery. Microsoft Research, 2009). In the same way, domain knowledge from information visualization, visual analytics, and exploratory search has found its way into the DL workflow. This trend is expected to continue, considering future DL challenges such as content-based access to new document types, visual search, and exploration for information landscapes, or big data in general. To cope with these challenges,
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