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

journal contribution
posted on 2023-05-20, 11:02 authored by Gallagher, RV, Falster, DS, Maitner, BS, Salguero-Gomez, R, Vandvik, V, Pearse, WD, Schneider, FD, Kattge, J, Poelen, JH, Madin, JS, Ankenbrand, MJ, Penone, C, Feng, X, Vanessa AdamsVanessa Adams, Alroy, J, Andrew, SC, Balk, MA, Bland, LM, Boyle, BL, Bravo-Avila, CH, Brennan, I, Carthey, AJR, Catullo, R, Cavazos, BR, Conde, DA, Chown, SL, Fadrique, B, Gibb, H, Halbritter, AH, Hammock, J, Hogan, JA, Holewa, H, Hope, M, Iversen, CM, Jochum, M, Kearney, M, Keller, A, Mabee, P, Manning, P, McCormack, L, Michaletz, ST, Park, DS, Perez, TM, Pineda-Munoz, S, Ray, CA, Rossetto, M, Sauquet, H, Sparrow, B, Spasojevic, MJ, Telford, RJ, Tobias, JA, Violle, C, Walls, R, Weiss, KCB, Westoby, M, Wright, IJ, Enquist, BJ
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.

History

Publication title

Nature Ecology and Evolution

Volume

4

Pagination

294-303

ISSN

2397-334X

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

Nature Publishing Group

Place of publication

United Kingdom

Rights statement

Copyright 2020 Springer Nature Limited

Repository Status

  • Restricted

Socio-economic Objectives

Environmental policy, legislation and standards not elsewhere classified

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