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PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

DOI:10.1029/2019PA003632
Authors:
Deborah Khider at University of Southern California
Deborah Khider
Julien Emile-Geay at University of Southern California
Julien Emile-Geay
Nicholas McKay at Northern Arizona University
Nicholas McKay
Yolanda Gil at University of Southern California
Yolanda Gil
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Abstract and Figures

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.
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PaCTS 1.0: A Crowdsourced Reporting Standard
for Paleoclimate Data
D. Khider
1,2
, J. Emile‐Geay
2
, N. P. McKay
3
, Y. Gil
1
, D. Garijo
1
, V. Ratnakar
1
,
M. Alonso‐Garcia
4
, S. Bertrand
5
, O. Bothe
6
, P. Brewer
7
, A. Bunn
8
, M. Chevalier
9
,
L. Comas‐Bru
10,11
, A. Csank
12
, E. Dassié
13
, K. DeLong
14
, T. Felis
15
, P. Francus
16
,
A. Frappier
17
, W. Gray
18
, S. Goring
19
, L. Jonkers
15
, M. Kahle
20
, D. Kaufman
3
,
N. M. Kehrwald
21
, B. Martrat
22,23
, H. McGregor
24
, J. Richey
25
, A. Schmittner
26
,
N. Scroxton
27
, E. Sutherland
28
, K. Thirumalai
29
, K. Allen
30
, F. Arnaud
31
, Y. Axford
32
,
T. Barrows
24
, L. Bazin
18
, S. E. Pilaar Birch
33
, E. Bradley
34
, J. Bregy
35
, E. Capron
36
,
O. Cartapanis
37
,H.‐W. Chiang
38
, K. M. Cobb
39
, M. Debret
40
, R. Dommain
41
,
J. Du
26
, K. Dyez
42
, S. Emerick
43
, M. P. Erb
3
, G. Falster
44
, W. Finsinger
45
,
D. Fortier
46
, Nicolas Gauthier
47
, S. George
48
, E. Grimm
49
, J. Hertzberg
50
,
F. Hibbert
51
, A. Hillman
52
, W. Hobbs
53
, M. Huber
54
, A. L. C. Hughes
55,56
,
S. Jaccard
37
, J. Ruan
57
, M. Kienast
58
, B. Konecky
59
, G. Le Roux
60
, V. Lyubchich
61
,
V. F. Novello
43
, L. Olaka
62
, J. W. Partin
63
, C. Pearce
64
, S. J. Phipps
65
, C. Pignol
31
,
N. Piotrowska
66
,M.‐S. Poli
67
, A. Prokopenko
68
, F. Schwanck
69
, C. Stepanek
70
,
G. E. A. Swann
71
, R. Telford
72
, E. Thomas
73
, Z. Thomas
74
, S. Truebe
75
,
L. von Gunten
76
, A. Waite
77
, N. Weitzel
78
, B. Wilhelm
79
, J. Williams
80
,
M. Winstrup
82
, N. Zhao
83
, and Y. Zhou
8
1
Information Sciences Institute, University of Southern California, Los Angeles, CA, USA,
2
Department of Earth Sciences,
University of Southern California, Los Angeles, CA, USA,
3
School of Earth and Sustainability, Northern Arizona
University, Flagstaff, AZ, USA,
4
Department of Geology, University of Salamanca, Salamanca, Spain,
5
Renard Centre of
Marine Geology, Ghent University, Ghent, Belgium,
6
Helmholtz‐Zentrum Geesthacht, Geesthacht, Germany,
7
Laboratory
of Tree‐Ring Research, Tuscon, AZ, USA,
8
Western Washington University, Bellingham, WA, USA,
9
University of
Lausanne, Lausanne, Switzerland,
10
School of Earth Sciences, University of College Dublin, Belfied, Ireland,
11
School of
Archaeology, Geography and Environmental Sciences, Reading University, Reading, UK,
12
Department of Geography,
University of Nevada, Reno, NV, USA,
13
CNRS, Bordeaux University, Bordeaux, France,
14
Louisiana State University,
Baton Rouge, LA, USA,
15
MARUM‐Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany,
16
Institut National de la Recherche Scientifique, Quebec City, Québec, Canada, Geosiences, Skidmore College, Saratoga
17
Springs, NY, USA,
18
Laboratoire des Sciences du Climat et de l'Environnement (LSCE/IPSL), Gif‐sur‐Yvette, France,
19
Department of Geography, Univerisity of Wisconsin‐Madison, Madison, WI, USA,
20
Physical Geography, University
Freiburg, Freiburg, Germany, Geosciences and Environmental Change Science Center, U.S. Geological Survey, Denver,
21
CO, USA,
22
Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research,
Spanish Council for Scientific Research, Barcelona, Spain,
23
Department of Earth Sciences, University of Cambridge,
Cambridge, UK,
24
School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, New South
Wales, Australia,
25
U.S. Geological Survey, St. Petersburg, FL, USA,
26
College of Earth, Ocean, and Atmospheric Sciences,
Oregon State University, Corvallis, OR, USA,
27
School of Earth Sciences, University College Dublin, Dublin, Ireland,
28
Rocky Mountain Research Station, U.S. Forest Service, Jemez Pueblo, NM, USA,
29
Department of Geosciences,
University of Arizona, Tucson, AZ, USA,
30
Department of Forest and Ecosystem Science, University of Melbourne,
Richmond, Victoria, Australia,
31
EDYTEM, Université Grenoble Alpes, University Savoie Mt Blanc, CNRS, Chambery,
France,
32
Department of Earth and Planetary Sciences, Northwestern University, Evanston, IL, USA,
33
Department of
Geography, University of Georgia, Athens, GA, USA,
34
Department of Computer Science, University of Colorado, Boulder,
Boulder, CO, USA,
35
Department of Geography, Indiana University Bloomington, Bloomington, IN, USA,
36
Physics of Ice,
Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark,
37
Institute of Geological
Sciences, University of Bern, Bern, Switzerland,
38
Department of Geosciences, National Taiwan University, Taipei City,
Taiwan,
39
School of Earth and Atmospheric Sciences, Georgia Tech, Atlanta, GA, USA,
40
Université de Rouen Normandie,
Mont‐Saint‐Aignan, France,
41
Institute of Geosciences, University of Potsdam, Potsdam, Germany,
42
Earth and
Environmental Sciences, University of Michigan, Ann Arbor, MI, USA,
43
Instituto de Geociências, Laboratório de Sistemas
Cársticos, Universidade de São Paulo, São Paulo, Brazil,
44
The University of Adelaide, Adelaide, South Australia, Australia,
45
ISEM, CNRS, University Montpellier, Montpellier, France,
46
Département de Géographie, Université de Montréal,
Montréal, Québec, Canada,
47
Shcool of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA,
48
National Center for Atmospheric Science (NCAS), Department of Meteorology, University of Reading, Reading, UK,
49
Department of Earth Sciences, University of Minnesota, Minneapolis, MN, USA,
50
Department of Ocean, Earth, and
©2019. American Geophysical Union.
All Rights Reserved.
FEATURE ARTICLE
10.1029/2019PA003632
Key Points:
•First version of a crowdsourced
reporting standard for paleoclimate
data
•The standards arose through
collective discussions, both in person
and online, and via an innovative
social platform
•The standard helps meet the
interoperability and reuse criteria of
FAIR (Findable, Accessible,
Interoperable, and Reusable)
Supporting Information:
•Supporting Information S1
•Data Set S1
Correspondence to:
D. Khider,
khider@usc.edu
Citation:
Khider, D., Emile‐Geay, J.,
McKay, N. P., Gil, Y., Garijo, D.,
Ratnakar, V., et al. (2019). PaCTS 1.0: A
crowdsourced reporting standard for
paleoclimate data. Paleoceanography
and Paleoclimatology,34,
Received 29 MAY 2019
Accepted 13 AUG 2019
Accepted article online 3 SEP 2019
KHIDER ET AL.
Williams ,
J. J.
81
4
Published online 201924 OCT
Corrected 21 FEB 2020
This article was corrected on 21 FEB
2020. See the end of the full text for
details.
1570
1–1 .
https://doi.org/10.1029/2019PA003632
570 596
... In paleoecological and paleoclimate studies, depending on the research aims or proxy employed, it has become commonplace that numerous independent cores are recovered, even from the same wetland or peatland (cf. Khider et al., 2019;Pfalz et al., 2021). Each study site establishes its own age-depth model independently by obtaining separate radiocarbon dates for independently selected layers. ...
... While scientists are still collecting new data from peatlands each year, thorough data handling of already existing datasets might help to fill remaining knowledge gaps of past changes (cf. Khider et al., 2019;Pfalz et al., 2021). However, the quality of different datasets may vary greatly, depending on different factors (cf. ...
... However, the quality of different datasets may vary greatly, depending on different factors (cf. Khider et al., 2019;Pfalz et al., 2021). When integrating these existing datasets into a coherent framework and reporting them in a standard form, high reproducibility and comparability are of the first and great importance. ...
A humification-based method toward refining Holocene radiocarbon chronologies: Wetland records from southeastern China
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Holocene paleoclimate reconstructions and comparisons largely rely on accurate age-depth modeling. However, uncertainties in chronology, such as those caused by sparse radiocarbon dates, will hamper inter-core comparisons and correlations, and might result in misleading “cause and consequence” conclusions. This study aimed to find a solution to increase the comparability and minimize the uncertainty of wetland chronology as much as possible. Sediment cores were recovered and radiocarbon dated from the Lianhuachi wetland located in Southeastern China. Humification degree and loss-on-ignition (LOI) were determined using colorimetric and combustion methods respectively. Our data were compared with previously published datasets obtained in the same wetland. The results show that independent humification profiles from the Lianhuachi wetland displayed high similarities. This high similarity between the humification profiles allowed us to transfer radiocarbon ages from one core to another using sequence slotting correlation. Applying the humification-based chronology refinement method to all sediment cores resulted in an improvement in the correlation coefficients between the same but independently measured proxy sequences from the wetland, which suggests both the inter- and intra-core comparability was improved. Because determining peat humification degree is easy, inexpensive, and time-saving, we suggest that humification can serve as a tool that can be used to correlate different cores and to transfer published radiocarbon ages within the same wetland (peatland) or in a comparable geological setting, to establish a more robust chronology of these comparable cores. The degree of peat humification can thus serve as a relative dating technique to refine the chronology of wetland (including peatland) records.
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... A set of concepts written in a standard syntax with widely agreed definitions to produce a lexical or taxonomic framework for knowledge representation that can be shared across various information technology communities. Brank et al. 2005 The fundamental data structure for comprehending knowledge Raskin and Pan 2005 A formal representation of technical concepts and their interrelationships in a way that supports domain knowledge Guarino et al. 2009 A special kind of information object or computational artifact García and Gil 2010 A clear alternative for formally representing content value chains and allowing copyright management solutions to be implemented on top of that formalization Arp et al. 2015 A representational artifact that includes a taxonomy and whose representations are intended to denote a set of universals, defined classes, and relationships between them Nasution 2018 Foundation of semantic Khider et al. 2019 Formal means of representing objects and their properties, and it represents consensus knowledge that allows a community to explain major concepts in a domain using common language. Khadir et al. 2021 The product of a shared body of information that has been organized in such a way that it can be read by machines and captures a specific conceptualization of the universe ...
... Crowdsourcing has evolved as a new approach for leveraging human knowledge and intelligence to complete activities that are difficult for computers to complete efficiently (Alabduljabbar and Al-Dossari, 2019). Therefore, for the past few years, crowdsourcing has been used in the creation and development of ontologies Khider et al., 2019;Waagmeester et al., 2020). ...
... Computers can now navigate through metadata and discover data that would otherwise be hidden from them using ontology (Khider et al., 2019). Artificial Intelligence (AI) enables the community to construct community infrastructure for effective data integration and analysis thanks to a consensual ontology that has been embraced. ...
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Big data generated by remote sensing, ground-based measurements, models and simulations, social media and crowdsourcing, and a wide range of structured and unstructured sources necessitates significant data and knowledge management efforts. Innovations and developments in information technology over the last couple of decades have made data and knowledge management possible for an insurmountable amount of data collected and generated over the last decades. This enabled open knowledge networks to be built that led to new ideas in scientific research and the business world. To design and develop open knowledge networks, ontologies are essential since they form the backbone of conceptualization of a given knowledge domain. A systematic literature review was conducted to examine research involving ontologies related to hydrological processes and water resource management. Ontologies in the hydrology domain support the comprehension, monitoring, and representation of the hydrologic cycle's complex structure, as well as the predictions of its processes. They contribute to the development of ontology-based information and decision support systems; understanding of environmental and atmospheric phenomena; development of climate and water resiliency concepts; creation of educational tools with artificial intelligence; and strengthening of related cyberinfrastructures. This review provides an explanation of key issues and challenges in ontology development based on hydrologic processes to guide the development of next generation artificial intelligence applications. The study also discusses future research prospects in combination with artificial intelligence and hydroscience.
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... Much of the discussion involving the establishment of standardised digitised data has revolved around defining an ideal database format and/or repository for the storage of data (Bolliet et al., 2016;Jonkers et al., 2020;Khider et al., 2019;McKay and Emile-Geay, 2016), which is indeed a key prerequisite for the ultimate end goal whereby all data is stored on a common, publicly searchable/queryable online database in line with the goals of FAIR data. ...
... The palaeoclimate literature has begun to embrace the principles of FAIR data and many good examples of useful database structures have been previously provided (Bolliet et al., 2016;Jonkers et al., 2020;Khider et al., 2019;McKay and Emile-Geay, 2016). We have provided an example of a concrete first step in the journey towards FAIR data, the creation of machine-readable data at the field and laboratory level. ...
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... We underscore that the data needed to undertake our analysis (top and bottom depths/ages) is not always included in other relevant databases (e.g., Neotoma or the Global Paleofire Database (Power et al., 2010;Williams et al., 2018)) which could provide a more globally representative dataset. This shortcoming highlights the need to adopt more comprehensive and standardized data reporting in paleofire research (Hawthorne et al., 2018;Khider et al., 2019). Nonetheless, the charcoal records we compiled are primarily derived from lacustrine sediments and vary in terms of their temporal resolution, span, and sample number (Table 1). ...
... Although our analyses have highlighted an important oversight in paleofire research, the bulk of currently available data is insufficiently reported to determine its full extent. We therefore recommend that these measurement details (top and bottom depth/age) be included in future datasets shared within these frameworks and that more comprehensive and standardized data reporting be adopted by paleofire practitioners (Hawthorne et al., 2018;Khider et al., 2019). ...
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... All of these issues hinder the investigation of large-scale temporal and geographic patterns because researchers must create both the data sets and analytical tools for each study in isolation, in contrast to the group of paleobiologists who generate open data as well as analysis and visualization tools built around those data (see the PBDB website's "Resources" section). The lack of a shared and integrated SOD database is a known issue in paleoceanography (e.g., Greene & Thirumalai, 2019) and has been a source of recent work (e.g., Khider et al., 2019). Establishing a community-led, open-source ecosystem of SOD fossil and stratigraphic data is vital for achieving many paleoceanography and marine sedimentary geology research goals, such as quantifying regional to global biodiversity (including the effects of mass extinction), food web interactions, and marine sedimentation and sediment subduction trends (i.e., Müller et al., 2022). ...
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... The resulting standard for describing paleoclimate data emerged over a period of 2 years, and there was great convergence on how to describe the different datasets as well as a few basic terms that were adopted by all (Khider et al. 2019). I should mention it was accomplished with zero face to face meetings, just a single meeting was held at the very beginning to agree to the overall process. ...
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... To do this, a set of criteria were adapted from the schemes of Lancaster et al. (2016) (INQUA Dunes Atlas chronologic database) and Small et al. (2017) (BRITICE-CHRONO). Following Khider et al. (2019)'s crowdsourced standards on metadata reporting, we recognise that caution needs to be taken when applying contemporary data reporting standards to previous research that was not subject to the same exacting standards as present, so we differentiate between criteria that are essential and those that are recommended. Table 3 details the information used to classify ages from Category 1 (meeting all essential and recommended criteria), Category 2 (meeting all essential criteria), and Category 3 (not meeting the essential criteria), where Category 1 and 2 represent ages that passed the chronological filtering. ...
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... Oftentimes, it is the attempts to integrate multi-proxy datasets that drives the establishment of standardized vocabularies, which enhance both interaction and discoverability (Morrill et al., 2021). In the light of FAIR principles, reporting standards are now being revisited, in some cases using crowd-sourced methods (e.g., PaCTS 1.0, (Paleoclimate Community reporting Standard) Khider et al., 2019). ...
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Radiometric dating methods are essential for developing geochronologies to study Late Quaternary environmental change and 210Pb dating is commonly used to produce age-depth models from recent (within 150 years) sediments and other geoarchives. The past two centuries are marked by rapid environmental socio-ecological changes frequently attributed to anthropogenic land-use activities, modified biogeochemical cycles, and climate change. Consequently, historical reconstructions over this recent time interval have high societal value because analyses of these datasets provide understanding of the consequences of environmental modifications, critical ecosystem thresholds, and to define desirable ranges of variation for management, restoration, and conservation. For this information to be used more broadly, for example to support land management decisions or to contribute data to regional analyses of ecosystem change, authors must report all of the useful age-depth model information. However, at present there are no guidelines for researchers on what information should be reported to ensure 210Pb data are fully disclosed, reproducible, and reusable; leading to a plethora of reporting styles, including inadequate reporting that reduces potential reusability and shortening the data lifecycle. For example, 64% of the publications in a literature review of 210Pb dated geoarchives did not include any presentation of age uncertainty estimates in modeled calendar ages used in age-depth models. Insufficient reporting of methods and results used in 210Pb dating geoarchives severely hampers reproducibility and data reusability, especially in analyses that make use of databased palaeoenvironmental data. Reproducibility of data is fundamental to further analyses of the number of palaeoenvironmental data and the spatial coverage of published geoarchives sites. We suggest, and justify, a set of minimum reporting guidelines for metadata and data reporting for 210Pb dates, including an IEDA (Interdisciplinary Earth Data Alliance), LiPD (Linked Paleo Data) and generic format data presentation templates, to contribute to improvements in data archiving standards and to facilitate the data requirements of researchers analyzing datasets of several palaeoenvironmental study sites. We analyze practices of methods, results and first order interpretation of 210Pb data and make recommendations to authors on effective data reporting and archiving to maximize the value of datasets. We provide empirical evidence from publications and practitioners to support our suggested reporting guidelines. These guidelines increase the scientific value of 210Pb by expanding its relevance in the data lifecycle. Improving quality and fidelity of environmental datasets broadens interdisciplinary use, lengthens the potential lifecycle of data products, and achieves requirements applicable for evidenced-based policy support.
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SISAL: Bringing Added Value to Speleothem Research
Article
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  • Feb 2019
Isotopic records from speleothems are an important source of information about past climates and, given the increase in the number of isotope-enabled climate models, are likely to become an important tool for climate model evaluation. SISAL (Speleothem Isotopes Synthesis and Analysis) have created a global database of isotopic records from speleothems in order to facilitate regional analyses and data-model comparison. The papers in this Special Issue showcase the use of the database for regional analyses. In this paper, we discuss some of the important issues underpinning the use of speleothems and how the existence of this database assists palaeoclimate research. We also highlight some of the lessons learned in the creation of the SISAL database and outline potential research going forward.
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The SISAL database: a global resource to document oxygen and carbon isotope records from speleothems
Article
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  • Aug 2018
Stable isotope records from speleothems provide information on past climate changes, most particularly information that can be used to reconstruct past changes in precipitation and atmospheric circulation. These records are increasingly being used to provide out-of-sample evaluations of isotope-enabled climate models. SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group of the Past Global Changes (PAGES) project. The working group aims to provide a comprehensive compilation of speleothem isotope records for climate reconstruction and model evaluation. The SISAL database contains data for individual speleothems, grouped by cave system. Stable isotopes of oxygen and carbon (δ¹⁸O, δ¹³C) measurements are referenced by distance from the top or bottom of the speleothem. Additional tables provide information on dating, including information on the dates used to construct the original age model and sufficient information to assess the quality of each data set and to erect a standardized chronology across different speleothems. The metadata table provides location information, information on the full range of measurements carried out on each speleothem and information on the cave system that is relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.17864/1947.147.
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Technical note: Open-paleo-data implementation pilot - The PAGES 2k special issue
Article
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Data stewardship is an essential element of the publication process. Knowing how to enact data polices that are described only in general terms can be difficult, however. Examples are needed to model the implementation of open-data polices in actual studies. Here we explain the procedure used to attain a high and consistent level of data stewardship across a special issue of the journal Climate of the Past. We discuss the challenges related to (1) determining which data are essential for public archival, (2) using data generated by others, and (3) understanding data citations. We anticipate that open-data sharing in paleo sciences will accelerate as the advantages become more evident and as practices that reduce data loss become the accepted convention.
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Enabling FAIR Data Across the Earth and Space Sciences
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  • Dec 2017
Data experts from publishers, repositories, and other organizations met last month to kick off a project to promote open and Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.
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A Controlled Crowdsourcing Approach for Practical Ontology Extensions and Metadata Annotations
Conference Paper
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  • Oct 2017
Traditional approaches to ontology development have a large lapse between the time when a user using the ontology has found a need to extend it and the time when it does get extended. For scientists, this delay can be weeks or months and can be a significant barrier for adoption. We present a new approach to ontology development and data annotation enabling users to add new metadata properties on the fly as they describe their datasets, creating terms that can be immediately adopted by others and eventually become standardized. This approach combines a traditional, consensus-based approach to ontology development, and a crowdsourced approach where expert users (the crowd) can dynamically add terms as needed to support their work. We have implemented this approach as a socio-technical system that includes: (1) a crowdsourcing platform to support metadata annotation and addition of new terms, (2) a range of social editorial processes to make standardization decisions for those new terms, and (3) a framework for ontology revision and updates to the metadata created with the previous version of the ontology. We present a prototype implementation for the Paleoclimate community, the Linked Earth Framework, currently containing 700 datasets and engaging over 50 active contributors. Users exploit the platform to do science while extending the metadata vocabulary, thereby producing useful and practical metadata.
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A global multiproxy database for temperature reconstructions of the Common Era
Article
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  • Jul 2017
Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
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Data reporting standards for publication of U-series data for geochronology and timescale assessment in the earth sciences
Article
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Uranium-series data provide essential dating and tracer tools for a broad spectrum of geologic processes. Data reported in U-series geochronology studies often contain insufficient information to completely assess the data collected. It is frequently not possible to calculate a date using the information provided or to re-calculate using different parameters, ultimately limiting the value of the data. The decay constants used are particularly important in that some of the relevant U-series isotopes have been revised. Here we provide a rationale for a minimum set of required data that will enable most calculations and facilitate later data comparisons. Along with these data reporting norms, we discuss additional metadata that will improve understanding of the data and also enhance the ability to re-interpret and assess them in the context of other studies. We posit that these recommendations will provide a foundation for increasing the longevity and usefulness of measurements in the discipline of U-series geochronology.
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