Advanced Data Visualization in Astrophysics: the X3D Pathway
Abstract
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.
Cite
@article{arxiv.1510.02796,
title = {Advanced Data Visualization in Astrophysics: the X3D Pathway},
author = {F. P. A. Vogt and C. I. Owen and L. Verdes-Montenegro and S. Borthakur},
journal= {arXiv preprint arXiv:1510.02796},
year = {2016}
}
Comments
11 pages, 6 figures, accepted for publication in ApJ. Associated Github repository: https://github.com/fpavogt/x3d-pathway (v0.9 release DOI:10.5281/zenodo.31953)