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ADVANCED DATA VISUALIZATION IN ASTROPHYSICS: THE X3D PATHWAY

2016; IOP Publishing; Volume: 818; Issue: 2 Linguagem: Inglês

10.3847/0004-637x/818/2/115

1538-4357

F. Vogt, Chris I. Owen, L. Verdes–Montenegro, Sanchayeeta Borthakur,

Data Analysis with R

Most modern astrophysical datasets are multi-dimensional; a characteristic that can nowadays generally be conserved and exploited scientifically during the data reduction/simulation and analysis cascades. Yet, the same multi-dimensional datasets are systematically cropped, sliced and/or projected to printable two-dimensional (2-D) diagrams at the publication stage. In this article, we introduce the concept of the "X3D pathway" as a mean of simplifying and easing the access to data visualization and publication via three-dimensional (3-D) diagrams. The X3D pathway exploits the facts that 1) the X3D 3-D file format lies at the center of a product tree that includes interactive HTML documents, 3-D printing, and high-end animations, and 2) all high-impact-factor & peer-reviewed journals in Astrophysics are now published (some exclusively) online. We argue that the X3D standard is an ideal vector for sharing multi-dimensional datasets, as it provides direct access to a range of different data visualization techniques, is fully-open source, and is a well defined ISO standard. Unlike other earlier propositions to publish multi-dimensional datasets via 3-D diagrams, the X3D pathway is not tied to specific software (prone to rapid and unexpected evolution), but instead compatible with a range of open-source software already in use by our community. The interactive HTML branch of the X3D pathway is also actively supported by leading peer-reviewed journals in the field of Astrophysics. Finally, this article provides interested readers with a detailed set of practical astrophysical examples designed to act as a stepping stone towards the implementation of the X3D pathway for any other dataset.