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Molecumentary: Scalable Narrated Documentaries Using Molecular Visualization

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Abstract

We present a method for producing documentary-style content using real-time scientific visualization. We produce molecumentaries, i.e., molecular documentaries featuring structural models from molecular biology. We employ scalable methods instead of the rigid traditional production pipeline. Our method is motivated by the rapid evolution of interactive scientific visualization, which shows great potential in science dissemination. Without some form of explanation or guidance, however, novices and lay-persons often find it difficult to gain insights from the visualization itself. We integrate such knowledge using the verbal channel and provide it along an engaging visual presentation. To realize the synthesis of a molecumentary, we provide technical solutions along two major production steps: 1) preparing a story structure and 2) turning the story into a concrete narrative. In the first step, information about the model from heterogeneous sources is compiled into a story graph. Local knowledge is combined with remote sources to complete the story graph and enrich the final result. In the second step, a narrative, i.e., story elements presented in sequence, is synthesized using the story graph. We present a method for traversing the story graph and generating a virtual tour, using automated camera and visualization transitions. Texts written by domain experts are turned into verbal representations using text-to-speech functionality and provided as a commentary. Using the described framework we synthesize automatic fly-throughs with descriptions that mimic a manually authored documentary. Furthermore, we demonstrate a second scenario: guiding the documentary narrative by a textual input.
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Dates and versions

hal-03022692 , version 1 (24-11-2020)

Licence

Attribution - ShareAlike - CC BY 4.0

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David Kouřil, Ondřej Strnad, Peter Mindek, Sarkis Halladjian, Tobias Isenberg, et al.. Molecumentary: Scalable Narrated Documentaries Using Molecular Visualization. 2020. ⟨hal-03022692⟩
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