This paper presents the current state of development of GlamMap, a visualisation tool that displays library metadata on an interactive, computer-generated geographic map. The focus in the paper is on the most crucial improvement achieved in the development of the tool: GlamMapping Trove. The visualisation of Trove’s sixtymillion book records is possible thanks to an improved database structure, more efficient data retrieval, and more scalable visualisation algorithms. The paper analyses problems encountered in visualising massive datasets, describes remaining challenges for the (...) tool, and presents a use case demonstrating GlamMap’s ability to serve researchers in the history of ideas. (shrink)

This paper presents GlamMap, a visualization tool for large, multi-variate georeferenced humanities data sets. Our approach visualizes the data as glyphs on a zoomable geographic map, and performs clustering and data aggregation at each zoom level to avoid clutter and to prevent overlap of symbols. GlamMap was developed for the Galleries, Libraries, Archives, and Museums (GLAM) domain in cooperation with researchers in philosophy. We demonstrate the usefulness of our approach by a case study on history of logic, which involves navigation (...) and exploration of 7100 bibliographic records, and scalability on a data set of sixty million book records. (shrink)

We propose a novel type of low distortion radial embedding which focuses on one specific entity and its closest neighbors. Our embedding preserves near-exact distances to the focus entity and aims to minimize distortion between the other entities. We present an interactive exploration tool SolarView which places the focus entity at the center of a "solar system" and embeds its neighbors guided by concentric circles. SolarView provides an implementation of our novel embedding and several state-of-the-art dimensionality reduction and embedding techniques, (...) which we adapted to our setting in various ways. We experimentally evaluated our embedding and compared it to these state-of-the-art techniques. The results show that our embedding competes with these techniques and achieves low distortion in practice. Our method performs particularly well when the visualization, and hence the embedding, adheres to the solar system design principle of our application. Nonetheless - as with all dimensionality reduction techniques - the distortion may be high. We leverage interaction techniques to give clear visual cues that allow users to accurately judge distortion. We illustrate the use of SolarView by exploring the high-dimensional metric space of bibliographic entity similarities. (shrink)