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Developing Virtual Reality Visualizations for Unsteady Flow Analysis of Dinosaur Track Formation using Scientific Sketching

Novotny, J, Tveite, J, Turner, M, Gatesy, S, Drury, F, Falkingham, PL and Laidlaw, D (2019) Developing Virtual Reality Visualizations for Unsteady Flow Analysis of Dinosaur Track Formation using Scientific Sketching. IEEE Transactions on Visualization and Computer Graphics, 25 (5). pp. 2145-2154. ISSN 1077-2626

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We present the results of a two-year design study to developing virtual reality (VR) flow visualization tools for the analysis of dinosaur track creation in a malleable substrate. Using Scientific Sketching methodology, we combined input from illustration artists, visualization experts, and domain scientists to create novel visualization methods. By iteratively improving visualization concepts at multiple levels of abstraction we helped domain scientists to gain insights into the relationship between dinosaur foot movements and substrate deformations. We involved over 20 art and computer science students from a VR design course in a rapid visualization sketching cycle, guided by our paleontologist collaborators through multiple critique sessions. This allowed us to explore a wide range of potential visualization methods and select the most promising methods for actual implementation. Our resulting visualization methods provide paleontologists with effective tools to analyze their data through particle, pathline and time surface visualizations. We also introduce a set of visual metaphors to compare foot motion in relation to substrate deformation by using pathsurfaces. This is one of the first large-scale projects using Scientific Sketching as a development methodology. We discuss how the research questions of our collaborators have evolved during the sketching and prototyping phases. Finally, we provide lessons learned and usage considerations for Scientific Sketching based on the experiences gathered during this project.

Item Type: Article
Additional Information: © 2019 IEEE.
Uncontrolled Keywords: 0801 Artificial Intelligence and Image Processing, 0802 Computation Theory and Mathematics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QE Geology > QE701 Paleontology
Divisions: Natural Sciences & Psychology (closed 31 Aug 19)
Publisher: IEEE
Date Deposited: 25 Mar 2019 15:05
Last Modified: 04 Sep 2021 09:35
DOI or ID number: 10.1109/TVCG.2019.2898796
URI: https://researchonline.ljmu.ac.uk/id/eprint/10402
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