How to build up big team science: a practical guide for large-scale collaborations

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The past decade has witnessed a proliferation of big team science (BTS), endeavours where a comparatively large number of researchers pool their intellectual and/or material resources in pursuit of a common goal. Despite this burgeoning interest, there exists little guidance on how to create, manage and participate in these collaborations. In this paper, we integrate insights from a multi-disciplinary set of BTS initiatives to provide a how-to guide for BTS. We first discuss initial considerations for launching a BTS project, such as building the team, identifying leadership, governance, tools and open science approaches. We then turn to issues related to running and completing a BTS project, such as study design, ethical approvals and issues related to data collection, management and analysis. Finally, we address topics that present special challenges for BTS, including authorship decisions, collaborative writing and team decision-making.

Related collections

Most cited references 57

Record: found
Abstract: found
Article: not found

Initial sequencing and analysis of the human genome.

E. S. Lander, L M Linton, B Birren … (2001)

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

0 comments Cited 1685 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

PSYCHOLOGY. Estimating the reproducibility of psychological science.

Brian Nosek, Rima-Maria Rahal, Marcus Munafo … (2016)

Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.

0 comments Cited 980 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.

Joseph P Simmons, Leif D Nelson, Uri Simonsohn (2011)

In this article, we accomplish two things. First, we show that despite empirical psychologists' nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.

0 comments Cited 864 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Heidi A. Baumgartner:

ORCID: http://orcid.org/0000-0001-5032-5995

Role: ConceptualizationRole: Formal analysisRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Nicolás Alessandroni:

ORCID: https://orcid.org/0000-0002-6595-0969