Illustration by Oliver Munday
An analysis of more than 50 collaborations shows the secrets of success, write Joel Cutcher-Gershenfeld and colleagues from the Stakeholder Alignment Collaborative.
By: Joel Cutcher-Gershenfeld, Karen S. Baker, Nicholas Berente, Courtney Flint, Gabriel Gershenfeld, Brandon Grant, Michael Haberman, John Leslie King, Christine Kirkpatrick, Barbara Lawrence, Spenser Lewis, W. Christover Lenhardt, Matthew Mayernik, Charles McElroy, Barbara Mittleman, Namchul Shin, Shelley Stall, Susan Winter and Ilya Zaslavsky.
"I am going to my grave with my disk drive in my cold dead hands." So a senior scientist told a junior researcher, who related the tale at a 2013 US National Science Foundation (NSF) workshop on the reuse of physical samples in the geosciences. Sharing - of data sets, metadata, models, software and other resources - promises to speed discoveries, improve reproducibility and expand economic development. But it requires people to change.
Overcoming personal reluctance is doubly difficult because many aspects of the scientific enterprise undermine sharing. Right now, most departments, funders and journals presume that data are proprietary from collection to publication. Even when individual scientists and institutional leaders want to do things differently, they face reviewers, colleagues and competitors clinging to conventional models.
As philosopher of science Thomas Kuhn documented more than 50 years ago, the scientific community resists challenges to its orthodoxy. The open sharing of data and other resources is a prime example1. Conservatism reigns because, as the 'iron law of oligarchy' devised by sociologist Robert Michel in the 1910s predicts, institutions established to achieve a certain goal will prioritize continued existence over the stated objective2. And we've all experienced 'path dependency': that practices are hard to change once established3. For example, despite widespread support, few academic departments have restructured tenure processes to accommodate interdisciplinary work.
Over the past four years, we have studied more than a dozen scientific consortia involved in data sharing, and we've mapped the landscape of these and another 44 such initiatives. When they work well, consortia act as catalysts, to accomplish what members cannot do alone4,5. But scientists are seldom taught effective strategies to design and manage such coalitions. Here we distil the lessons from our fieldwork into five ways to foster open science.
The authors describe CyVerse (then the iPlant Collaborative):
"Consortia enable science and the infrastructure for sharing data to co-evolve. The iPlant Collaborative was funded by the NSF in 2008 to build a platform linking high-performance computing centers to plant scientists. Initial participation was disappointing: they built it, but people didn't come.
As the science changed, high-performance computing was needed for genomic data, and usage increased dramatically. In fact, the resources proved useful beyond botanical data. So, in 2015, iPlant expanded its focus to become CyVerse, which provides infrastructure for very large data sets and complex analyses across the life sciences. This was a deliberate shift in step with changing science, and broadened the collaborative's impact."