Scholarly Data Share: A Model for Sharing Big Data in Academic Research

The Scholarly Data Share (SDS) is a lightweight web interface that facilitates access to large, curated research datasets stored in a tape archive. SDS addresses the common needs of research teams working with and managing large and complex datasets, and the associated storage. The service adds several key features to the standard tape storage offerings that are of particular value to the research community: (1) the ability to capture and manage metadata, (2) metadata-driven browsing and retrieval over a web interface, (3) reliable and scalable asynchronous data transfers, and (4) an interface that hides the complexity of the underlying storage and access infrastructure. SDS is designed to be easy to implement and sustain over time by building on existing tool chains and proven open-source software and by minimizing bespoke code and domain-specific customization. In this paper, we describe the development of the SDS and the implementation of an instance to provide access to a large collection of geospatial datasets.