In the era of Big Data, research productivity can be highly sensitive to the availability of large scale, long term archival storage. Unfortunately, many mass storage systems are prohibitively expensive at scales appropriate for individual institutions rather than for national centers. Furthermore, a key issue is the set of circumstances under which researchers can, and are willing to, adopt a centralized technology that, in a pure cost recovery model, might be, or might appear to be, more expensive than what the research teams could build on their own. This paper examines a business model that addresses these concerns in a comprehensive manner, distributing the costs among a funding agency, the institution and the research teams, thereby reducing the challenges faced by each.