Open Science principles for accelerating trait-based science across the Tree of Life

Gallagher, Rachael V.; Falster, Daniel S.; Maitner, Brian S.; Salguero-Gómez, Roberto; Vandvik, Vigdis; Pearse, William D.; Schneider, Florian D.; Kattge, Jens; Poelen, Jorrit H.; Madin, Joshua S.; Ankenbrand, Markus J.; Penone, Caterina; Feng, Xiao; Adams, Vanessa M.; Alroy, John; Andrew, Samuel C.; Balk, Meghan A.; Bland, Lucie M.; Boyle, Brad L.; Bravo-Avila, Catherine H.; ... (2020). Open Science principles for accelerating trait-based science across the Tree of Life. Nature ecology & evolution, 4(3), pp. 294-303. Springer Nature 10.1038/s41559-020-1109-6

[img] Text
s41559-020-1109-6.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (1MB)

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) > Plant Ecology
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS)

UniBE Contributor:

Penone, Caterina, Jochum, Malte, Manning, Peter

Subjects:

500 Science > 580 Plants (Botany)

ISSN:

2397-334X

Publisher:

Springer Nature

Language:

English

Submitter:

Peter Alfred von Ballmoos-Haas

Date Deposited:

24 Mar 2020 16:23

Last Modified:

05 Dec 2022 15:37

Publisher DOI:

10.1038/s41559-020-1109-6

BORIS DOI:

10.7892/boris.141261

URI:

https://boris.unibe.ch/id/eprint/141261

Actions (login required)

Edit item Edit item
Provide Feedback