Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

Abstract

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators

“…A 2003 report of a National Science Foundation (NSF) blue-ribbon panel, headed by Daniel Atkins, popularized the term cyberinfrastructure to describe systems of data storage, software, high performance computing (HPC), and people who can solve scientific problems of the size and scope presented by big data [ 7 ]. The report was the impetus for several cyberinfrastructure projects in the biological sciences, including the NSF’s CyVerse, the Department of Energy’s KBase, and the European Grid Infrastructure and the European Life Sciences Infrastructure for Biological Information (ELIXIR) [ 8 ]. The Atkins Report described cyberinfrastructure as the means to harness the data revolution and to develop a “knowledge economy.” Although people were acknowledged as active elements of cyberinfrastructure, few published studies have assessed how well their computational and cyberinfrastructure needs are being met.…”

Data-aware optimization of bioinformatics workflows in hybrid clouds

“…In the era of Big data, cost-efficient high performance computing is proving to be the only viable option for most scientific disciplines [14]. Bioinformatics is one of the most representative fields in this area, as the data explosion has overwhelmed current hardware capabilities.…”

Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

“…To enable data-driven research, healthcare, and thus CD, there are approaches to support the distribution of analytics over distributed data (often related to the terms distributed analytics or federated learning). For this, new solutions such as grid/cloud computing have been proposed [21]. Moreover, software solutions such as i2b2 or DataShield support analyzing sensitive data in a distributed fashion [22,23].…”