Project 702 In a Nutshell
Science today is facing a dilemma of data volume. With modern scientific instruments producing enormous volumes of data per minute, there is a driving need to find efficient methods of storing and analysing experimental data. Using global climate data as a case study, we explore a traditional file-based architecture and compare it to a database-centered architecture for the efficient storage and analysis of high-volumes of data. We examine the potential limitations in terms of scalability and manageability and discuss the benefits of integrating database technology within data-intensive sciences. Finally, we consider the potential technical and social barriers to adopting relational database technology in the sciences.