  Distributed communities of researchers rely increasingly on valuable,
proprietary, or sensitive datasets. Given the growth of such data, especially
in fields new to data-driven, computationally intensive research like the
social sciences and humanities, coupled with what are often strict and complex
data-use agreements, many research communities now require methods that allow
secure, scalable and cost-effective storage and analysis. Here we present CLOUD
KOTTA: a cloud-based data management and analytics framework. CLOUD KOTTA
delivers an end-to-end solution for coordinating secure access to large
datasets, and an execution model that provides both automated infrastructure
scaling and support for executing analytics near to the data. CLOUD KOTTA
implements a fine-grained security model ensuring that only authorized users
may access, analyze, and download protected data. It also implements automated
methods for acquiring and configuring low-cost storage and compute resources as
they are needed. We present the architecture and implementation of CLOUD KOTTA
and demonstrate the advantages it provides in terms of increased performance
and flexibility. We show that CLOUD KOTTA's elastic provisioning model can
reduce costs by up to 16x when compared with statically provisioned models.
