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The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource

  • John W. Williams (a1) (a2), Eric C. Grimm (a3), Jessica L. Blois (a4), Donald F. Charles (a5), Edward B. Davis (a6), Simon J. Goring (a1), Russell W. Graham (a7), Alison J. Smith (a8), Michael Anderson (a9), Joaquin Arroyo-Cabrales (a10), Allan C. Ashworth (a11), Julio L. Betancourt (a12), Brian W. Bills (a13), Robert K. Booth (a14), Philip I. Buckland (a15), B. Brandon Curry (a16), Thomas Giesecke (a17), Stephen T. Jackson (a18), Claudio Latorre (a19), Jonathan Nichols (a20), Timshel Purdum (a21), Robert E. Roth (a1) (a22), Michael Stryker (a12) and Hikaru Takahara (a23)...
Abstract

The Neotoma Paleoecology Database is a community-curated data resource that supports interdisciplinary global change research by enabling broad-scale studies of taxon and community diversity, distributions, and dynamics during the large environmental changes of the past. By consolidating many kinds of data into a common repository, Neotoma lowers costs of paleodata management, makes paleoecological data openly available, and offers a high-quality, curated resource. Neotoma’s distributed scientific governance model is flexible and scalable, with many open pathways for participation by new members, data contributors, stewards, and research communities. The Neotoma data model supports, or can be extended to support, any kind of paleoecological or paleoenvironmental data from sedimentary archives. Data additions to Neotoma are growing and now include >3.8 million observations, >17,000 datasets, and >9200 sites. Dataset types currently include fossil pollen, vertebrates, diatoms, ostracodes, macroinvertebrates, plant macrofossils, insects, testate amoebae, geochronological data, and the recently added organic biomarkers, stable isotopes, and specimen-level data. Multiple avenues exist to obtain Neotoma data, including the Explorer map-based interface, an application programming interface, the neotoma R package, and digital object identifiers. As the volume and variety of scientific data grow, community-curated data resources such as Neotoma have become foundational infrastructure for big data science.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
*Corresponding author at: Department of Geography, 550 North Park St., University of Wisconsin-Madison, Madison, Wisconsin 53706, USA. E-mail address: jww@geography.wisc.edu (J.W. Williams).
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**

J.W. Williams and E.C. Grimm contributed equally to this manuscript.

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