From Reductionism to Reintegration: Solving society's most pressing problems requires building bridges between data types across the life sciences.

Anne E Thessen,Melissa A Haendel,Paul Bogdan,Orlando De Lange,David J Patterson,Theresa M Casey,César Hinojo-Hinojo

doi:10.1371/journal.pbio.3001129

Abstract

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a “Data as a Service”-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.

Highlights

Life on Earth is an interplay of interacting biological systems and geological processes that evolved over approximately 3 billion years and is represented by more than 2 million extant species
Contributor Attribution Model (CAM) builds on the work of groups like CASRAI [71] by using CRediT [72] to inform the Contributor Role Ontology—the source of role terms in CAM [73]. (Domain-specific groups like CASRAI are an integral part of developing the community standards discussed above.) There are a few existing systems for recording attribution such as ORCID [74], OpenVIVO [75], and rescognito [76] that have begun to tackle the issue of credit for data work
Our ability to address issues that draw on many subdisciplines of biology will improve with integrated access to data across diverse types

Summary

Introduction

Life on Earth is an interplay of interacting biological systems and geological processes that evolved over approximately 3 billion years and is represented by more than 2 million extant species. The development of a service-oriented DaaS architecture with appropriate human expertise and technical infrastructure will improve integration of currently separated data and enable transdisciplinary collaboration. The key to integrated data among silos is the universal adoption of community-developed standards [45] (Box 2).

Results

Conclusion