With computational humanities relying heavily on proprietary APIs and legacy code environments that become obsolete within a few years, long-term reproducibility has emerged as an acute archival crisis.
Where should digital scholarship teams draw the line between archiving static research datasets versus actively maintaining executable research software environments?
