An Assistive Tool for Authoring Visualization Thumbnails

Department of Computer Science and EngineeringVisualization of data is continuously stimulating for its potential to describe narratives inside data. It is a well-known medium in the digital era for expressing the insights of data. In recent times, storytelling in data-driven articles that comes under the category of data journalism is significantly adapting by news organizations. However, current data-driven visualization thumbnail tools either are lacking support for extracting the information from documents that contain unstructured text, tables, and graphical data and telling the story on it or require expressive technical expertise. Therefore, I introduce an integrated authoring tool, which is a combination of model and user interface. The objective of this study is to simplify the informative thumbnail creation process in the field of journalism. Generally, the current prevailing systems involve manually selecting and formatting entity from textual or tabular source, a process that leads to being tiresome and error-prone. Furthermore, there is no tool exist that extracts the insights from the document???s unstructured text, tables and graphics data simultaneously and provides graphical visuals for thumbnail or static visualization. With VTComp, data-driven news article contents are automatically extracted and converted into graphics and formatted textual layout, to enable journalists for further usage of results. We presented a user interface, which consists of all the essential components required for narrative visualization. Our system expresses the data insights with separate categories like summary text, graphical response view which contains chart visuals and document related visuals differentiated by label text and the final output of the system is interactive static visual graphics contributed by machine and user. By enabling storytelling without programming, the VTComp interface overcomes the interaction gap between user and system-generated results. We evaluated VTComp through multiple measurements such as benchmark comparison of automatically extraction of target entities against manual extraction, and system compatibility with different news organizations??? data-driven articles. Besides, an introductory evaluation of the user experience of thumbnail authoring using iPad and touch pencil by performing user study session and a follow-up quantitative and qualitative analysis. Finally, The results of the user study acknowledge that VTComp beneficial for journalists to create the data-rich and informative graphics, thumbnails from an unstructured text document with-in a short period, ithout any special expertise and efforts.clos