Boundary Spanning, Data and Software Curation, and Cyberinfrastructure Deployment: Dimensions for Developing Science Gateways

Abstract

<div>There are many incentives to repurpose science cyberinfrastructure capabilities developed for one domain application for use in another domain. These incentives include funder programmatic goals, potential efficiencies through reuse, generative value creating new science, and supporting scientific reproducibility. </div><div><br></div><div>Whether you call it the process crossing the ‘valley of death’, tech infusion, or developing a science gateway, challenges bringing data science, computer science, and domain science experts together to create a domain specific science platform based on existing capabilities can be a frustrating and laborious process with no guarantee of success. These challenges may be fundamental as communicating and translating a concept from one domain to another, or finding a common basis of understanding to transfer domain knowledge and technical knowledge between the two communities, or instilling leading edge curation and development practices. </div><div><br></div><div>This poster outlines the approach that the Renaissance Computing Institute has developed to address these aspects of these challenges. RENCI uses both technical side and the knowledge side to bridge these gaps. More specifically, RENCI’s hybrid approach includes, technology hardening and refactoring, an interoperable technology stack driven by rules and policies, and a focus on boundary objects and boundary, spanning project expertise. RENCI’s experience developing science cyberinfrastructure has contributed to the development of our approach. </div><div><br></div><div>Our poster will describe how these methods have been developed and deployed in the context of a number of RENCI projects including iRODS (Integrated Rule Oriented Data System, {xDCI}Share (Cross-domain cyberinfrastructure), and Risk Analytics Discovery Environment (RADE). In addition to describing the application and methods, we will also share some lessons learned along the way in the context of RENCI projects. </div

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