OCR
76 | Digital Media and Storytelling in Higher Education recipient with the capability to specify the variables which are shown on the graph. One such responsive visual is the US gun homicide interface (see above), where the recipient can make a comparative analysis using variables such as gender, age, ethnicity, region, type of weapon, and the relationship between murderers and victims. Similar interactive interfaces have also appeared during the COVID-19 pandemic. The WHO's coronavirus information interface features a classic sequential dashboard layout, but the visualization of relevant trends is responsive: users can access additional information by selecting charts and maps, and can activate filters by moving their mouse.* Similar interactive visualizations are available from the Danish public media, with data updated daily.” A further example of interactive DDS is NASAs visualization of a time machine showing the parameters ofthe Earth” which allows the viewer to create a narrative that is relevant to their own.” Explanatory visualizations, which do not support interactivity, pre-interpret data from a particular perspective, focusing on certain aspects ofthe data to create a relationship and narrative sequence between them. Visualizations that include exploratory aspects, on the other hand, give recipients flexibility by allowing them to choose the perspective and the order in which to view the data. This flexibility can help readers find their own meaning in the visualization (Thudt et al., 2018). Presenting data using a narrative framework is a complex undertaking. Chevalier et al. (2018) reconstructed the process of DDS based on semistructured interviews with nine professionals, including researchers, graphic designers, and journalists. They found that DDS is a serious collaborative task that requires a range of skills, such as application knowledge and collaborative skills. As in all research, the work starts with data collection, cleaning, and interpretation. The creative team needs to find relevant results and connections in the data set in order to develop the right approach through which to explore the relationships in the data. The right visualization also requires the research team to experiment with different visualization types and place them in context. The data team and the storytelling team need to work in close collaboration to achieve an impactful final result (Figure 6). % https://covidi9.who.int/ 36 https://www.dr.dk/nyheder/indland/status-paa-coronavirus-lige-nu 7 https://climate.nasa.gov/interactives/climate-time-machine 38 https://climate.nasa.gov/earth-now/#/