We propose a use and reuse driven big data management approach that fuses the data repository and data processing capabilities in a co-located, public cloud. It answers to the urgent data management needs from the growing number of researchers who don’t fit in the big science/small science dichotomy. This approach will allow researchers to more easily use, manage, and collaborate around big data sets, as well as give librarians the opportunity to work alongside the researchers to preserve and curate data while it is still fresh and being actively used. This also provides the technological foundation to foster a sharing culture more aligned with the open source software development paradigm than the lone-wolf, gift-exchanging small science sharing or the top-down, highly structured big science sharing.

To materialize this vision, we provide a system architecture consisting of a scalable digital repository system coupled with the co-located cloud storage and cloud computing, as well as a job scheduler and a deployment management system. Motivated by Virginia Tech’s Goodwin Hall instrumentation project, we implemented and evaluated a prototype. The results show not only sufficient capacities for this particular case, but also near perfect linear storage and data processing scalabilities under moderately high workload.