  Careful preservation of experimental data, simulations, analysis products,
and theoretical work maximizes their long-term scientific return on investment
by enabling new analyses and reinterpretation of the results in the future. Key
infrastructure and technical developments needed for some high-value science
targets are not in scope for the operations program of the large experiments
and are often not effectively funded. Increasingly, the science goals of our
projects require contributions that span the boundaries between individual
experiments and surveys, and between the theoretical and experimental
communities. Furthermore, the computational requirements and technical
sophistication of this work is increasing. As a result, it is imperative that
the funding agencies create programs that can devote significant resources to
these efforts outside of the context of the operations of individual major
experiments, including smaller experiments and theory/simulation work. In this
Snowmass 2021 Computational Frontier topical group report (CompF7:
Reinterpretation and long-term preservation of data and code), we summarize the
current state of the field and make recommendations for the future.
