This document discusses publicly-funded research software, algorithms, and workflows. It argues that software is fundamentally different than data and requires different policies regarding public access. The document outlines that a large portion of research is software-intensive and relies on software. However, software faces sustainability issues like "software collapse" if not actively maintained. The document recommends that funding agencies take steps to incentivize open source software and long-term maintenance through funding and career incentives. It suggests defaulting to open source models but allowing other options if justified, with the goal of software remaining useful over time beyond the initial funding period.