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Christof Pearce

PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

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DOI

  • D. Khider, University of Southern California
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  • P. Brewer, Laboratory of Tree-Ring Research
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  • E. Dassié, Universite Bordeaux
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  • K. DeLong, Louisiana State University (LSU)
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  • W. Gray, Universite Paris-Saclay
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  • S. Goring, University of Wisconsin-Madison
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  • L. Jonkers, University of Bremen
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  • M. Kahle, University of Freiburg
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  • D. Kaufman, Northern Arizona University
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  • N. M. Kehrwald, United States Geological Survey
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  • B. Martrat, CSIC, University of Cambridge
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  • H. McGregor, University of Wollongong
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  • J. Richey, United States Geological Survey
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  • A. Schmittner, Oregon State University
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  • N. Scroxton, University College Dublin
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  • E. Sutherland, Rocky Mountain Research Station
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  • K. Thirumalai, University of Arizona
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  • K. Allen, University of Melbourne
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  • F. Arnaud, Universite Grenoble Alpes
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  • Y. Axford, Northwestern University
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  • T. Barrows, University of Wollongong
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  • L. Bazin, Universite Paris-Saclay
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  • S. E. Pilaar Birch, The University of Georgia
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  • E. Bradley, University of Colorado Boulder
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  • J. Bregy, Indiana University
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  • E. Capron, Niels Bohr Institute
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  • O. Cartapanis, University of Bern
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  • H. W. Chiang, National Taiwan University
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  • K. M. Cobb, Georgia Institute of Technology
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  • M. Debret, Universite de Rouen
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  • R. Dommain, Universität Potsdam
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  • J. Du, Oregon State University
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  • K. Dyez, University of Michigan, Ann Arbor
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  • S. Emerick, Universidade de Sao Paulo
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  • M. P. Erb, Northern Arizona University
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  • G. Falster, University of Adelaide
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  • W. Finsinger, Universite de Montpellier
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  • D. Fortier, HEC Montréal (Université de Montréal)
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  • Nicolas Gauthier, Arizona State University
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  • S. George, University of Reading
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  • E. Grimm, University of Minnesota
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  • J. Hertzberg, Old Dominion University
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  • F. Hibbert, Australian National University
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  • A. Hillman, University of Louisiana at Lafayette
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  • W. Hobbs, University of Tasmania
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  • M. Huber, Purdue University
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  • A. L.C. Hughes, Manchester University, University of Bergen
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  • S. Jaccard, University of Bern
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  • J. Ruan, Sun Yat-Sen University
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  • M. Kienast, Dalhousie University
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  • B. Konecky, Washington University St. Louis
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  • G. Le Roux, Universite de Toulouse
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  • V. Lyubchich, Maryland University
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  • V. F. Novello, Universidade de Sao Paulo
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  • L. Olaka, University of Nairobi
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  • J. W. Partin, University of Texas at Austin
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  • C. Pearce
  • S. J. Phipps, University of Tasmania
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  • C. Pignol, Universite Grenoble Alpes
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  • N. Piotrowska, Silesian University of Technology
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  • M. S. Poli, Eastern Michigan University
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  • A. Prokopenko, University of Cologne
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  • F. Schwanck, Universidade Federal do Rio Grande do Sul
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  • C. Stepanek, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
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  • G. E.A. Swann, University of Nottingham
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  • R. Telford, University of Bergen
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  • E. Thomas, British Antarctic Survey
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  • Z. Thomas, University of New South Wales
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  • S. Truebe, Arizona State Parks and Trails
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  • L. von Gunten, PAGES International Project Office
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  • A. Waite, ANGARI Foundation
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  • N. Weitzel, Universität Heidelberg
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  • B. Wilhelm, Universite Grenoble Alpes
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  • J. Williams, University of Wisconsin-Madison
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  • M. Winstrup, University of Copenhagen
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  • N. Zhao, Max Planck Institute for Chemistry
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  • Y. Zhou, Columbia University

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.

Original languageEnglish
JournalPaleoceanography and Paleoclimatology
Volume34
Issue10
Pages (from-to)1570-1596
Number of pages27
ISSN2572-4517
DOIs
Publication statusPublished - 1 Jan 2019

    Research areas

  • best practices, data, FAIR, paleoceanography, paleoclimate, standards

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