Stefan Jänicke

On Close and Distant Reading in Digital Humanities: A Survey and Future Challenges

We present an overview of the last ten years of research on visualizations that support close and distant reading of textual data in the digital humanities. We look at various works published within both the visualization and digital humanities communities. We provide a taxonomy of applied methods for close and distant reading, and illustrate approaches that combine both reading techniques to provide a multifaceted view of the data. Furthermore, we list toolkits and potentially beneficial visualization approaches for research in the digital humanities. Finally, we summarize collaboration experiences when developing visualizations for close and distant reading, and give an outlook on future challenges in that research area.

Visual Text Analysis in Digital Humanities

In 2005, Franco Moretti introduced Distant Reading to analyse entire literary text collections. This was a rather revolutionary idea compared to the traditional Close Reading, which focuses on the thorough interpretation of an individual work. Both reading techniques are the prior means of Visual Text Analysis. We present an overview of the research conducted since 2005 on supporting text analysis tasks with close and distant reading visualizations in the digital humanities. Therefore, we classify the observed papers according to a taxonomy of text analysis tasks, categorize applied close and distant reading techniques to support the investigation of these tasks and illustrate approaches that combine both reading techniques in order to provide a multi‐faceted view of the textual data. In addition, we take a look at the used text sources and at the typical data transformation steps required for the proposed visualizations. Finally, we summarize collaboration experiences when developing visualizations for close and distant reading, and we give an outlook on future challenges in that research area.

GeoTemCo: Comparative Visualization of Geospatial-Temporal Data with Clutter Removal Based on Dynamic Delaunay Triangulations

The amount of online data annotated with geospatial and temporal metadata has grown rapidly in the recent years. Providers like Flickr and Twitter are popular, but hard to browse. Many systems exist that, in multiple linked views, show the data under geospatial, temporal, and topical aspects. We unify and extend these systems in a Web application to support comparison of multiple, potentially large result sets of textual queries with extended interaction capabilities. We present a novel fast algorithm using a dynamic Delaunay triangulation for merging glyphs in the map view into so-called circle groups to avoid visual clutter, which is critical for the comparative setting. We evaluate our design by qualitative comparison with existing systems.

TagSpheres: Visualizing Hierarchical Relations in Tag Clouds

Tag clouds are widely applied, popular visualization techniques as they illustrate summaries of textual data in an intuitive, lucid manner. Many layout algorithms for tag clouds have been developed in the recent years, but none of these approaches is designed to reflect the notion of hierarchical distance. For that purpose, we introduce a novel tag cloud layout called TagSpheres. By arranging tags on various hierarchy levels and applying appropriate colors, the importance of individual tags to the observed topic gets assessable. To explore relationships among various hierarchy levels, we aim to place related tags closely. Three usage scenarios from the digital humanities, sports and aviation, and an evaluation with humanities scholars exemplify the applicability and point out the benefit of TagSpheres.

On the Visualization of Hierarchical Relations and Tree Structures with TagSpheres

Tag clouds are widely applied, popular visualization techniques as they illustrate summaries of textual data in an intuitive, lucid manner. Many layout algorithms for tag clouds have been developed in the recent years, but none of these approaches is designed to reflect the notion of hierarchical distance. For that purpose, we introduce a novel tag cloud layout called TagSpheres. By arranging tags on various hierarchy levels and applying appropriate colors, the importance of individual tags to the observed topic gets assessable. To explore relationships among various hierarchy levels, we aim to place related tags closely. Various usage scenarios from the digital humanities, sports, aviation and natural disaster management point out the benefit of TagSpheres for different domains. In addition, we highlight that TagSpheres is also a novel layout approach for tree structures.

Designing Close and Distant Reading Visualizations for Text Re-use

We present various visualizations for the Text Re-use found among texts of a collection to support answering a broad palette of research questions in the humanities. When juxtaposing all texts of a corpus in form of tuples, we propose the Text Re-use Grid as a distant reading method that emphasizes text tuples with systematic or repetitive Text Re-use. The Text Re-use Browser provides a closer look on the Text Re-use between the two texts of a tuple. Additionally, we present Text Re-use Alignment Visualizations to improve the readability of Text Variant Graphs that are used to compare various text editions to each other. Finally, we illustrate the benefit of the proposed visualizations with four usage scenarios for various topics in literary criticism.

TagPies: Comparative Visualization of Textual Data.

A TagPie is a novel tag cloud layout that arranges the tags belonging to multiple data categories in a pie chart manner. Motivated from research in classical philology, TagPies were designed to support the comparative analysis of classical terminology. In this scenario, the data categories represent the co-occurrences of different searched keywords, so that the comparison of the contexts in which these keywords were used becomes possible using TagPies. This paper illustrates the iterative development of TagPies, which aid as a distant reading view on a text corpus for humanities scholars. We outline various steps of our collaborative digital humanities project, and we emphasize the utility of the proposed design by outlining various usage scenarios representing current research questions in classical philology.

Visualizing Mouvance: Toward a visual analysis of variant medieval text traditions

Medieval literary traditions provide a particularly challenging test case for textual alignment and the visualization of variance. Whereas the editors of medieval traditions working with the printed page struggle to illustrate the complex phenomena of textual instability, research in screen-based visualization has made significant progress, allowing for complex textual situations to be captured at the microand the macro-level. This article uses visualization and a computational approach to identifying variance to allow the analysis of different medieval poetic works using the transcriptions of how they are found in particular manuscripts. It introduces the notion of a meso-level visualization, a visual representation of aligned text providing for comparative reading on the screen, all the while assembling non-contradictory, intuitive solutions for the visual exploration of multi-scalar variance. Building upon the literary notion of mouvance, it delves into medieval French literature and, in particular, different visualizations of three versions of the Chanson de Roland (the Oxford, the Châteauroux, and the Venice 4 manuscripts). The article presents experimental prototypes for such meso-level visualization and explores how they can advance our understanding of formulaically rich medieval poetry. .................................................................................................................................................................................

A Directed Concept Search Environment to Visually Explore Texts Related to User-defined Concept Models

We introduce a concept search environment that caters for the needs of humanities scholars who want to improve the accuracy of search results when querying historical text corpora. For this purpose, we designed a so-called Concept Editor that allows to model historical concepts in a diagram style according to the imaginations of the humanities scholar. For the inspection of results determined in the proposed concept search, we provide a Concept Search Results Viewer that uses the existent layout of the underlying concept model to visualize related texts according to the relevance to the given concept. We further designed the overall system the way that the humanities scholar can iteratively refine the concept idea, which leads to a gradual improvement of search results. To illustrate the whole development pipeline, we provide a usage scenario on modeling the concept epilepsy with the purpose of improving the accuracy of results compared to usual applied keyword-based search methods.