Data-centric Perspective Research Articles

New Software Engineering Requirements in Clouds and Large-Scale Systems

The primary IT paradigm has changed from a compute-centric to a data-centric problem perspective. For decades our whole IT concepts were building around the foundation laid out by von Neumann. As the memory wall, parallelism, dynamicity, and multitenancy become the predominating factors in modern application performance and capabilities, this foundation doesn't hold true anymore. Rather than building up new layers, a complete rethinking of the software engineering principles is in order to overcome the essential issues in the long run. This article provides an overview over the core problems and the different approaches to overcome them.

In recent issues

Over recent years, there has been exciting growth in collaboration between academia and industry in the life sciences to make data more Findable, Accessible, Interoperable and Reusable (FAIR) to achieve greater value. Despite considerable progress, the transformative shift from an application-centric to a data-centric perspective, enabled by FAIR implementation, remains very much a work in progress on the ‘FAIR journey’. In this review, we consider use cases for FAIR implementation. These can be deployed alongside assessment of data quality to maximize the value of data generated from research, clinical trials, and real-world healthcare data, which are essential for the discovery and development of new medical treatments by biopharma.