English

iDaVIE v1.0: A virtual reality tool for interactive analysis of astronomical data cubes

Instrumentation and Methods for Astrophysics 2026-03-17 v1 Astrophysics of Galaxies Human-Computer Interaction

Abstract

As modern astronomy confronts unprecedented data volumes, automated pipelines and machine-learning techniques have become essential for processing and analysis. As these workflows grow more complex, astronomers also require input and inspection tools that can keep pace. To address challenges in navigating multidimensional datasets for quality control and scientific interpretation, we present the immersive Data Visualisation Interactive Explorer (iDaVIE), a virtual reality (VR) software suite developed in collaboration with the astronomy community. iDaVIE enables users to import and render large 3D data cubes within a VR environment, offering real-time tools for selection, cropping, catalogue overlays, and exporting results back into existing pipelines. Built on the Unity engine and SteamVR, the system uses custom plug-ins for efficient data parsing, downsampling, and statistical calculations. The software has already been integrated into workflows such as verifying HI data cubes from MeerKAT, ASKAP, and APERTIF, refining detection masks, and identifying new sources. Its intuitive interface aims to reduce the cognitive load associated with higher-dimensional data, allowing researchers to focus more directly on scientific goals. As an open-source, scalable, and adaptable platform, iDaVIE supports continued development and integration with other tools. Version 1.0 marks a significant milestone, with planned enhancements including subcube loading, advanced rendering modes, video-generation scripts, and collaborative capabilities. By pairing immersive visualisation with robust interaction tools, iDaVIE seeks to transform how researchers engage with complex datasets and enhance productivity in the era of big data.

Keywords

Cite

@article{arxiv.2603.15490,
  title  = {iDaVIE v1.0: A virtual reality tool for interactive analysis of astronomical data cubes},
  author = {Alexander Sivitilli and Lucia Marchetti and Angus Comrie and P. Cilliers Pretorius and Thijs and van der Hulst and Fabio Vitello and D. J. Pisano and Ugo Becciani and A. Russell Taylor and Paolo Serra and Mayhew Steyn and Michaela van Zyl},
  journal= {arXiv preprint arXiv:2603.15490},
  year   = {2026}
}

Comments

54 pages, 13 figures. Accepted for publication in Astronomy & Computing