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

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Authors: Alexander K. Sivitilli, L. Marchetti, Angus Comrie, P. Cilliers Pretorius, Thijs (J.M.) van der Hulst, Fabio Vitello, DJ Pisano, U. Becciani, A. Russell Taylor, P. Serra, Mayhew Steyn, Michaela Van Zyl
Cited by: 2
References: 27

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 need 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), an immersive 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. iDaVIE 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 aims to transform how researchers engage with complex datasets and enhance productivity in the era of big data.

Fields of Study & Subjects

Scientific Computing and Data Management Data Visualization and Analytics Data Analysis with R

Publication details

Journal / source
Astronomy and Computing
Publisher
Elsevier BV
Volume
56
Pages
101109–101109
Publication date
11 March 2026
Language
EN