Our paper, entitled “Towards Designing Unbiased Replication Studies in Information Visualization” was accepted to the BELIV 20018 Workshop and will be presented by lead author, Poorna Talkad Sukumar on October 21, 2018 in Berlin, Germany.
In this paper, we review 16 replication studies in Information Visualization and draw guidelines for helping researchers make unbiased and meaningful decisions when designing their replication studies. The paper can be downloaded here.
Ronald A. Metoyer, Qiyu Zhi, Bartosz Janczjuk, Walter Scheirer
Online writers and journalism media are increasingly combining visualization (and other multimedia content) with narrative text to create narrative visualizations. Often, however, the two elements are presented independently of one another. We propose an approach to automatically integrate text and visualization elements. We begin with a writer’s narrative that presumably can be supported with visual data evidence. We leverage natural language processing, quantitative narrative analysis, and information visualization to (1) automatically extract narrative components (who, what, when, where) from data-rich stories, and (2) integrate the supporting data evidence with the text to develop a narrative visualization. We also employ bidirectional interaction from text to visualization and visualization to text to support reader exploration in both directions. We demonstrate the approach with a case study in the data-rich field of sports journalism.