A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

TL;DR

This survey examines the current state and future needs of software ecosystems at Oak Ridge National Laboratory to support sustainable, community-driven scientific software for experimental and observational science, considering evolving hardware and data management.

Contribution

It provides a comprehensive survey framework and insights to guide development of sustainable, adaptable scientific software ecosystems at ORNL.

Findings

Identified key areas of interest and gaps in current EOS software.

Highlighted the need for community-based, reusable software solutions.

Outlined future challenges related to hardware heterogeneity and data management.

Abstract

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.