Teaming up as domain scientists and research software engineers for a sustainable HELIOS++ scientific software

The Heidelberg LiDAR Operations Simulator (HELIOS) is a scientific software for high-fidelity general-purpose virtual laser scanning (VLS) [1]. Using models for virtual scenes, scanner devices, and platforms, HELIOS allows to reproduce diverse scan scenarios over various geographical environments (forests, cities, mountains) and laser scanning systems (airborne and UAV-borne, mobile, terrestrial). Used for algorithm development, data acquisition planning, and method training for supervised machine learning, HELIOS has been successfully integrated into research workflows across the international laser scanning community.

HELIOS was initially developed in a research-driven environment in Java and released as open-source software [2]. Motivated by growing interest in the scientific community, the codebase was re-implemented in C++ to improve its memory footprint, runtime performance and functionality [3]. Since then, we are actively developing new features. Recent additions include support for dynamic scenes [4], new deflector mechanisms, and plug-ins for other open-source software such as Blender. Considering the continually growing user community, current software development specifically prioritizes quality assurance, reliability, long-term maintainability, and user-friendliness.

Supported by the DFG under the program "Research Software - Quality Assured and Re-usable" [5], the HELIOS++ developer team partnered up with the Scientific Software Center (SSC), a research software engineering service department at Heidelberg University. Combining the expertise of the domain scientist from the HELIOS team and the research software engineers (RSEs) of the SSC, we are strengthening the sustainability and usability of HELIOS. Measures presented in our talk include: Improving testing strategies and Continuous Integration, rewriting the CMake build system, packaging HELIOS as a Conda package, creating standalone installers, introducing a new Python API, and developing new strategies for sharing and reproducing HELIOS simulations. Additionally, we will reflect on the benefits as well as key challenges in fostering fruitful collaborations between domain scientists and RSEs. To this end, we will present as a domain scientist/RSE tandem.

References:

[1] HELIOS++: https://github.com/3dgeo-heidelberg/helios

[2] Bechtold, S., & Höfle, B. (2016): https://doi.org/10.5194/isprs-annals-III-3-161-2016

[3] Winiwarter, L et al. (2022): https://doi.org/10.1016/j.rse.2021.112772

[4] Weiser, H., & Höfle, B. (2026): https://doi.org/10.1111/2041-210x.70189

[5] Project website: https://www.geog.uni-heidelberg.de/en/3dgeo/projects-of-the-3dgeo-research-group/fostering-a-community-driven-and-sustainable-helios-scientific-software