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PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

PaCTS 1.0: معيار الإبلاغ الجماعي لبيانات المناخ القديم

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Oct 2019Embargo end date: 24 Apr 2020 Australia, United Kingdom, Germany, Australia, France, United States, France, France, Germany, Australia, Switzerland, France, Canada, United States, France, Denmark, Australia, France, Spain, Germany, France, France, United States, France, Norway, France Publisher:American Geophysical Union (AGU)Journal:Paleoceanography and Paleoclimatology, volume 34, pages 1,570-1,596 (issn: 2572-4517, eissn: 2572-4525,

Authors: D. Khider; J. Emile‐Geay; N. P. McKay; Y. Gil; D. Garijo; V. Ratnakar; M. Alonso‐Garcia; +86 Authors

PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

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Abstract

AbstractThe 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.

Countries

Australia, United Kingdom, Germany, Australia, France, United States, France, France, Germany, Australia, Switzerland, France, Canada, United States, France, Denmark, Australia, France, Spain, Germany, France, France, United States, France, Norway, France

Related Organizations

Spanish National Research Council
Spain
University of Melbourne
Australia
Louisiana State University
United States
National Taiwan University of Arts
Taiwan
University of Georgia
Georgia

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Keywords

FOS: Computer and information sciences, Data Sharing, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, 550, Paleoclimate, 910, Oceanography, palaeoceanography, Data science, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, [SDE.ES] Environmental Sciences/Environment and Society, best practices, Climate change, FAIR, Data, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Species Distribution Modeling and Climate Change Impacts, anzsrc-for: 3709 Physical Geography and Environmental Geoscience, Ecology, Ecological Modeling, forestry, anzsrc-for: 37 Earth Sciences, Geology, ddc:no, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, 004, World Wide Web, data, Physical Sciences, standards, Institut für Geowissenschaften, [SDV.SA.SF] Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, environment, Information Systems, Standards, Best practices, Science, [SDE.MCG]Environmental Sciences/Global Changes, best practice, 530, palaeoclimate, 333, [SDV.BV.BOT] Life Sciences [q-bio]/Vegetal Biology/Botanics, Data Sharing and Stewardship in Science, Paleoceanography, paleoclimate, [SDE.ES]Environmental Sciences/Environment and Society, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Paleoclimatology, 550 Earth sciences & geology, Metadata, ddc:550, Data Science, Paleontology, 37 Earth Sciences, FOS: Earth and related environmental sciences, 3709 Physical Geography and Environmental Geoscience, [SDE.ES]Environmental Sciences/Environmental and Society, Computer science, Standardization, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.MCG] Environmental Sciences/Global Changes, Operating system, Geological Sciences, FOS: Biological sciences, paleoceanography, Environmental Science, Computer Science, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Environmental DNA in Biodiversity Monitoring

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	30
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%