Data-Intensive Research

Edinburgh Data-Intensive Research Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis, and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively. They fail for several reasons, all of which are aspects of scalability. The deluge of computational methods and plethora of computational systems prevents effective and efficient use of resources, user interfaces are not adopted at a sufficient rate to satisfy demand for scientific computing and data and knowledge is created outside suitable contexts for collaborative research to be effective.

The Edinburgh Data-Intensive Research group addresses these scalability issues by providing mappings from abstract formulations to concrete and optimised executions of research challenges, by developing intuitive interfaces to enable access to steer these executions and by developing systems to aid in creating new research challenges. In this talk I will present several exemplars where we have dealt with scalability issues in scientific scenarios.