Data Sharing and Scientific Impact in Eddy Covariance Research. Issue 4 (16th April 2018)

• Record Type: Journal Article
• Authors: Bond‐Lamberty, B.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 4(2018)
• Page Start: 1440
• Page End: 1443
• Publication Date: 2018-04-16
• Subjects: eddy covariance -- open data -- data sharing -- open science; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1002/2018JG004502
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Do the benefits of data sharing outweigh its perceived costs? This is a critical question, and one with the potential to change culture and behavior. Dai et al. (2018, https://doi.org/10.1002/2017JG004277 ) examined how data sharing is related to scientific impact in the field of eddy covariance (EC) and found that data sharers are disproportionately high‐impact researchers, and vice versa; they also note strong regional differences in EC data‐sharing norms. The current policies and restrictions of EC journals and repositories are highly uneven. Incentivizing data sharing and enhancing computational reproducibility are critical next steps for EC, ecology, and science more broadly. Plain Language Summary: The raw data that scientists generate—typically from experiments and/or observations—have traditionally been kept private, but research funders, journals, and scientists themselves are pushing for change, arguing that taxpayer‐funded data should be "open" (available to all) on both moral and practical grounds. Do influential scientists share more, and does data sharing lead to higher impact? This commentary discusses a recent paper examining these issues in a particular field of ecology and earth system science. Current policies and restrictions are highly uneven, and it is critical to provide proper credit for scientists who freely share their data. Key Points: Data sharers are disproportionately high‐impact researchers, but the causality is uncertain Institutional support for data sharing in eddy covariance research is uneven Incentivizing data sharing and enhancing computational reproducibility are critical next steps