This research examines the use of data visualization not only to inform audiences about a particular event but mainly to humanize data and uncover the missing content and hidden stories. This research uses digital storytelling as an engaging tool to represent how the British newspaper, The Guardian, depicted the British Mad Cow Disease Crisis from 1986 to 1996. By incorporating a set of recent theories, such as thick data, local data and feminist data visualization, this research emphasizes the need to contextualize data so that these theories can help to fill the context-loss gap generated in standard data analysis. Employing the mixed methodologies of practice-based research, mapping as research, and research through design, this thesis comprises: 1) a written document stating the research process; 2) a series of iterations leading to an interactive web-based data story. The final storytelling aims to answer the questions of how we might represent the British Mad Cow Disease Crisis from 1986 to 1996 using a digital technique to approach different understandings of this historical event and how digital technologies and media benefit users and evoke their emotions.