Curation and Analysis of Global Sedimentary Geochemical Data to Inform Earth History

Akshay Mehra

Dartmouth College, Dept. of Earth Sciences, Hanover, New Hampshire 03755, USA, Akshay.K.Mehra@dartmouth.edu

C. Brenhin Keller

Dartmouth College, Dept. of Earth Sciences, Hanover, New Hampshire 03755, USA

Tianran Zhang

Dept. of Earth Sciences, Dartmouth College, Hanover, New Hampshire 03755, USA

Nicholas J. Tosca

Dept. of Earth Sciences, University of Cambridge, Cambridge CB2 1TN, UK

Scott M. McLennan

State University of New York, Stony Brook, New York 11794, USA

Erik Sperling

Dept. of Geological Sciences, Stanford University, Stanford, California 94305, USA

Una Farrell

Dept. of Geology, Trinity College Dublin, Dublin, Ireland

Jochen Brocks

Research School of Earth Sciences, Australian National University, Canberra, Australia

Donald Canfield

Nordic Center for Earth Evolution (NordCEE), University of Southern Denmark, Denmark

Devon Cole

School of Earth and Atmospheric Science, Georgia Institute of Technology, Atlanta, Georgia 30332, USA

Peter Crockford

Earth and Planetary Science, Weizmann Institute of Science, Rehovot, Israel

Huan Cui

Equipe Géomicrobiologie, Université de Paris, Institut de Physique, Paris, France, and Dept. of Earth Sciences, University of Toronto, Ontario M5S, Canada

Tais W. Dahl

GLOBE Institute, University of Denmark, Copenhagen, Denmark

Keith Dewing

Natural Resources Canada, Geological Survey of Canada, Calgary, Ontario T2L 2A7, Canada

Joseph F. Emmings

British Geological Survey, Nicker Hill, Keyworth, Nottingham NG12 5GG, UK

Robert R. Gaines

Dept. of Geology, Pomona College, Claremont, California 91711, USA

Tim Gibson

Dept. of Earth & Planetary Sciences, Yale University, New Haven, Connecticut 06520, USA

Geoffrey J. Gilleaudeau

Atmospheric, Oceanic, and Earth Sciences, George Mason University, Fairfax, Virginia 22030, USA

Romain Guilbaud

Géosciences Environnement Toulouse, CNRS, Toulouse, France

Malcolm Hodgskiss

Dept. of Geological Sciences, Stanford University, Stanford, California 94305, USA

Amber Jarrett

Onshore Energy Directorate, Geoscience Australia, Australia

Pavel Kabanov

Natural Resources Canada, Geological Survey of Canada, Calgary T2L 2A7, Canada

Marcus Kunzmann

Mineral Resources, CSIRO, Kensington, Australia

Chao Li

State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China

David K. Loydell

School of the Environment, Geography and Geosciences, University of Portsmouth, Portsmouth PO1 2UP, UK

Xinze Lu

Dept. of Earth and Environmental Sciences, University of Waterloo, Waterloo N2L 3G1, Canada

Austin Miller

Dept. of Earth and Environmental Sciences, University of Waterloo, Waterloo N2L 3G1, Canada

N. Tanner Mills

Dept. of Geology and Geophysics, Texas A&M University, College Station, Texas 77843, USA

Lucas D. Mouro

Geology Dept., Federal University of Santa Catarina, Santa Catarina State, Brazil

Brennan O’Connell

School of Earth Sciences, University of Melbourne, Melbourne, Australia

Shanan E. Peters

Dept. of Geoscience, University of Wisconsin–Madison, Madison 53706, Wisconsin, USA

Simon Poulton

School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK

Samantha R. Ritzer

Dept. of Geological Sciences, Stanford University, Stanford, California 94305, USA

Emmy Smith

Dept. of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland 21218, USA

Philip Wilby

British Geological Survey, Nicker Hill, Keyworth, Nottingham NG12 5GG, UK

Christina Woltz

Dept. of Earth Science, University of California, Santa Barbara, California 93106, USA

Justin V. Strauss

Dept. of Earth Sciences, Dartmouth College, Hanover, New Hampshire 03755, USA

Abstract

Large datasets increasingly provide critical insights into crustal and surface processes on Earth. These data come in the form of published and contributed observations, which often include associated metadata. Even in the best-case scenario of a carefully curated dataset, it may be non-trivial to extract meaningful analyses from such compilations, and choices made with respect to filtering, resampling, and averaging can affect the resulting trends and any interpretation(s) thereof. As a result, a thorough understanding of how to digest, process, and analyze large data compilations is required. Here, we present a generalizable workflow developed using the Sedimentary Geochemistry and Paleoenvironments Project database. We demonstrate the effects of filtering and weighted resampling on Al₂O₃ and U contents, two representative geochemical components of interest in sedimentary geochemistry (one major and one trace element, respectively). Through our analyses, we highlight several methodological challenges in a “bigger data” approach to Earth science. We suggest that, with slight modifications to our workflow, researchers can confidently use large collections of observations to gain new insights into processes that have shaped Earth’s crustal and surface environments.

Manuscript received 28 Sept. 2020. Revised manuscript received 2 Dec. 2020. Manuscript accepted 20 Feb. 2021. Posted 24 Mar. 2021.

© The Geological Society of America, 2021. CC-BY-NC.

https://doi.org/10.1130/GSATG484A.1