Documentary narrative visualization is a data visualization approach using the features of documentary film. Researchers in the field of visualization are searching for better methods of constructing narratives from data sets. In this article, we explore the structure and techniques of documentary film and how they apply to the practice of constructing narrative visualization with video. We review the structural aspects of documentary film with examples relevant for narrative visualization. Using six of the highest quality video-based narrative visualizations, we conducted a study of user preferences for three pairs of videos. The video pairs were specifically matched to highlight unique features available in documentary film. Using the preferences expressed by our participants, we performed an empirical study to examine the documentary features most valued by our participants. Our results provide implications about the style and features of documentary film that are most useful in the construction of narrative visualization. Overall, this work provides a clear starting point for the construction of documentary narrative visualization providing content creators with specific techniques that will improve engagement of their content.
RenovM. First-person films: some theses on self-inscription. New York: McGraw Hill, 2008.
15.
VertovD. Kino-eye: the writings of Dziga Vertov. Berkeley, CA: University of California Press, 1984.
16.
PandeyAVManivannanANovO, et al. The persuasive power of data visualization. IEEE T Vis Comp Graph2014; 3120(12): 2211–2220.
17.
AminiFHenry RicheNLeeB, et al. Understanding data videos: looking at narrative visualization through the cinematography lens. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, Seoul, Republic of Korea, 18–23 April 2015, pp. 1459–1468. New York: ACM.
18.
AminiFRicheNHLeeB, et al. Authoring data-driven videos with dataclips. IEEE T Vis Comp Graph2016; 23(1): 501–510.
Aristotle RobertsW. Rhetoric. New York: Random House, 1984.
32.
MorrisE. The thin blue line [Film]. Buffalo, NY: Miramax, 1988.
33.
BusselDJRosettA. Contract law and its application: cases and materials. New York: Foundation Press, 2006.
34.
SpurlockM. Super size me [Motion picture]. New York: Samuel Goldwyn Films, 2004.
35.
ShonJHKimYGYimSJ. Classifying movies based on audience perceptions: MTI framework and box office performance. J Media Eco2014; 27(2): 79–106.
36.
XieLChangSFDivakaranA, et al. Unsupervised mining of statistical temporal structures in video. In:RosenfeldADoermannDDeMenthonD (eds) Video mining. Boston, MA: Springer, 2003, pp. 279–307.
ZhouHFishbachA. The pitfall of experimenting on the web: how unattended selective attrition leads to surprising (yet false) research conclusions. J Personal Soc Psychol2016; 111(4): 493–504.
51.
FishwickP. Modeling as the practice of representation. In: Proceedings of the 2017 winter simulation conference (WSC), Las Vegas, NV, 3–6 December 2017, pp. 4276–4287. New York: IEEE.
52.
WhiteKIngallsR. The basics of simulation. In: Proceedings of the 2018 winter simulation conference (WSC), Gothenburg, 9–12 December 2018, pp. 147–161. New York: IEEE.
53.
BoyJDetienneFFeketeJD. Storytelling in information visualizations: does it engage users to explore data? In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, Seoul, Republic of Korea, 18–23 April 2015, pp. 1449–1458. New York: ACM.
54.
BradburyJGuadagnoR. Enhanced narratives. Manuscript submitted for publication.
