Issue 1, 2023

Collaborative methods to enhance reproducibility and accelerate discovery

Abstract

Many domains across physical, life, and social sciences suffer from incomplete models of constructs (e.g., organisms, environments, behaviors), which hinders reproducibility and the pace of discovery. Critically, the prevailing research paradigm, of individuals or small groups working within the resource constraints of their own organization, does little to support model completion and discovery. It does not integrate capabilities, enable investigators to generate data at scale, or offer a path to sharing knowledge at the level of data (versus at the level of conclusions). To develop and deploy a new paradigm for conducting science, The Defense Advanced Research Projects Agency (DARPA) created the Synergistic Discovery and Design (SD2) program. The SD2 program proposed a novel method of conducting science that (1) integrates the capabilities of multiple organizations across multiple domains and (2) makes implicit knowledge explicit at all stages of the scientific process. It assembled and integrated a sociotechnical system that aimed to overcome the limitations of conventional scientific methods. In this paradigm, scientists and technologists collaborated to develop technologies, share data, and conduct science in ways that were faster, more efficient, more complete, and more productive than was possible outside of this program. This paper describes the SD2 approach to developing that sociotechnical system—of selectively applying conventional methods of science, embracing a more collaborative paradigm, and establishing an infrastructure—to drive discovery.

Graphical abstract: Collaborative methods to enhance reproducibility and accelerate discovery

Article information

Article type
Perspective
Submitted
24 Jun 2022
Accepted
22 Nov 2022
First published
29 Nov 2022
This article is Open Access
Creative Commons BY-NC license

Digital Discovery, 2023,2, 12-27

Collaborative methods to enhance reproducibility and accelerate discovery

D. A. Leins, S. B. Haase, M. Eslami, J. Schrier and J. T. Freeman, Digital Discovery, 2023, 2, 12 DOI: 10.1039/D2DD00061J

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