Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"

Crystal-Ornelas, Robert; Varadharajan, Charuleka; Bond-Lamberty, Ben; Boye, Kristin; Cholia, Shreyas; Crow, Michael; Devarakonda, Ranjeet; Ely, Kim S.; Goldman, Amy; Heinz, Susan; Hendrix, Valerie; Damerow, Joan; Pennington, Stephanie; Burrus, Madison; Kakalia, Zarine; Robles, Emily; Simmonds, Maegen; Rogers, Alistair; Velliquette, Terri; Weierbach, Helen; Weisenhorn, Pamela; Welch, Jessica N.; Agarwal, Deborah A.

doi:10.15485/1780565

Title: Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"

Dataset
Other Related Research

Abstract

These data are the results of a systematic review that investigated how data standards and reporting formats are documented on the version control platform GitHub. Our systematic review identified 32 data standards in earth science, environmental science, and ecology that use GitHub for version control of data standard documents. In our analysis, we characterized the documents and content within each of the 32 GitHub repositories to identify common practices for groups that version control their documents on GitHub.In this data package, there are 8 CSV files that contain data that we characterized from each repository, according to the location within the repository. For example, in 'readme_pages.csv' we characterize the content that appears across the 32 GitHub repositories included in our systematic review. Each of the 8 CSV files has an associated data dictionary file (names appended with '_dd.csv' and here we describe each content category within CSV files.There is one file-level metadata file (flmd.csv) that provides a description of each file within the data package.

Authors:

;

Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
Lawrence Berkeley National Laboratory
Pacific Northwest National Laboratory (PNNL)
SLAC National Accelerator Laboratory
Lawrence Berkeley National Lab - NERSC
Oak Ridge National Laboratory
Brookhaven National Lab
Lawrence Livermore National Laboratory
PNNL
Argonne National Laboratory

Publication Date:: Thu Dec 31 23:00:00 EST 2020

Other Number(s):: ESD PRE-PUB DOI:10.15485/1780565

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; Environmental Systems Science Data Infrastructure for a Virtual Ecosystem

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; FAIR data; TRUST principles; data reporting formats; data repositories; data standards; metadata; open science

OSTI Identifier:: 1780565

DOI:: https://doi.org/10.15485/1780565

Citation Formats


                    Crystal-Ornelas, Robert, Varadharajan, Charuleka, Bond-Lamberty, Ben, Boye, Kristin, Cholia, Shreyas, Crow, Michael, Devarakonda, Ranjeet, Ely, Kim S., Goldman, Amy, Heinz, Susan, Hendrix, Valerie, Damerow, Joan, Pennington, Stephanie, Burrus, Madison, Kakalia, Zarine, Robles, Emily, Simmonds, Maegen, Rogers, Alistair, Velliquette, Terri, Weierbach, Helen, Weisenhorn, Pamela, Welch, Jessica N., and Agarwal, Deborah A. Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats".  United States: N. p., 2020. 
        Web.  doi:10.15485/1780565.

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                    Crystal-Ornelas, Robert, Varadharajan, Charuleka, Bond-Lamberty, Ben, Boye, Kristin, Cholia, Shreyas, Crow, Michael, Devarakonda, Ranjeet, Ely, Kim S., Goldman, Amy, Heinz, Susan, Hendrix, Valerie, Damerow, Joan, Pennington, Stephanie, Burrus, Madison, Kakalia, Zarine, Robles, Emily, Simmonds, Maegen, Rogers, Alistair, Velliquette, Terri, Weierbach, Helen, Weisenhorn, Pamela, Welch, Jessica N., & Agarwal, Deborah A. Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats".  United States.  doi:https://doi.org/10.15485/1780565

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                    Crystal-Ornelas, Robert, Varadharajan, Charuleka, Bond-Lamberty, Ben, Boye, Kristin, Cholia, Shreyas, Crow, Michael, Devarakonda, Ranjeet, Ely, Kim S., Goldman, Amy, Heinz, Susan, Hendrix, Valerie, Damerow, Joan, Pennington, Stephanie, Burrus, Madison, Kakalia, Zarine, Robles, Emily, Simmonds, Maegen, Rogers, Alistair, Velliquette, Terri, Weierbach, Helen, Weisenhorn, Pamela, Welch, Jessica N., and Agarwal, Deborah A. 2020.  
"Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"".  United States.  doi:https://doi.org/10.15485/1780565.  https://www.osti.gov/servlets/purl/1780565. Pub date:Thu Dec 31 23:00:00 EST 2020

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@article{osti_1780565,

  title        = {Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"},

  author       = {Crystal-Ornelas, Robert and Varadharajan, Charuleka and Bond-Lamberty, Ben and Boye, Kristin and Cholia, Shreyas and Crow, Michael and Devarakonda, Ranjeet and Ely, Kim S. and Goldman, Amy and Heinz, Susan and Hendrix, Valerie and Damerow, Joan and Pennington, Stephanie and Burrus, Madison and Kakalia, Zarine and Robles, Emily and Simmonds, Maegen and Rogers, Alistair and Velliquette, Terri and Weierbach, Helen and Weisenhorn, Pamela and Welch, Jessica N. and Agarwal, Deborah A.},

  abstractNote = {These data are the results of a systematic review that investigated how data standards and reporting formats are documented on the version control platform GitHub. Our systematic review identified 32 data standards in earth science, environmental science, and ecology that use GitHub for version control of data standard documents. In our analysis, we characterized the documents and content within each of the 32 GitHub repositories to identify common practices for groups that version control their documents on GitHub.In this data package, there are 8 CSV files that contain data that we characterized from each repository, according to the location within the repository. For example, in 'readme_pages.csv' we characterize the content that appears across the 32 GitHub repositories included in our systematic review. Each of the 8 CSV files has an associated data dictionary file (names appended with '_dd.csv' and here we describe each content category within CSV files.There is one file-level metadata file (flmd.csv) that provides a description of each file within the data package.},

  doi          = {10.15485/1780565},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Thu Dec 31 23:00:00 EST 2020},

  month        = {Thu Dec 31 23:00:00 EST 2020}

}

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DOI: https://doi.org/10.15485/1780565

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