Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data

Prakash, Giri; Shrestha, Biva; Younkin, Katarina; Jundt, Rolanda; Martin, Mark; Elliott, Jannean

doi:10.3390/data1020011

Title: Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data

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Abstract

The Atmospheric Radiation Measurement (ARM) Data Archive established a data citation strategy based on Digital Object Identifiers (DOIs) for the ARM datasets in order to facilitate citing continuous and diverse ARM datasets in articles and other papers. This strategy eases the tracking of data provided as supplements to articles and papers. Additionally, it allows future data users and the ARM Climate Research Facility to easily locate the exact data used in various articles. Traditionally, DOIs are assigned to individual digital objects (a report or a data table), but for ARM datasets, these DOIs are assigned to an ARM data product. This eliminates the need for creating DOIs for numerous components of the ARM data product, in turn making it easier for users to manage and cite the ARM data with fewer DOIs. In addition, the ARM data infrastructure team, with input from scientific users, developed a citation format and an online data citation generation tool for continuous data streams. As a result, this citation format includes DOIs along with additional details such as spatial and temporal information.

Authors:

Prakash, Giri ^[1]; Shrestha, Biva ^[1]; Younkin, Katarina ^[2]; Jundt, Rolanda ^[2];

^[3];

^[3]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
DOE Office of Scientific and Technical Information, Oak Ridge, TN (United States)

Publication Date:: Wed Aug 31 00:00:00 EDT 2016

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1319231

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: Data

Additional Journal Information:: Journal Volume: 1; Journal Issue: 2; Journal ID: ISSN 2306-5729

Publisher:: MDPI

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; atmospheric radiation measurement; DOIs; digital object identifier; data citation; arm data citation; continuous data citation

Citation Formats


                    Prakash, Giri, Shrestha, Biva, Younkin, Katarina, Jundt, Rolanda, Martin, Mark, and Elliott, Jannean. Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data.  United States: N. p., 2016. 
Web.  doi:10.3390/data1020011.

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                    Prakash, Giri, Shrestha, Biva, Younkin, Katarina, Jundt, Rolanda, Martin, Mark, & Elliott, Jannean. Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data.  United States.  https://doi.org/10.3390/data1020011

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                    Prakash, Giri, Shrestha, Biva, Younkin, Katarina, Jundt, Rolanda, Martin, Mark, and Elliott, Jannean. Wed .  
"Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data".  United States.  https://doi.org/10.3390/data1020011.  https://www.osti.gov/servlets/purl/1319231.

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@article{osti_1319231,

  title        = {Data always getting bigger -- A scalable DOI architecture for big and expanding scientific data},

  author       = {Prakash, Giri and Shrestha, Biva and Younkin, Katarina and Jundt, Rolanda and Martin, Mark and Elliott, Jannean},

  abstractNote = {The Atmospheric Radiation Measurement (ARM) Data Archive established a data citation strategy based on Digital Object Identifiers (DOIs) for the ARM datasets in order to facilitate citing continuous and diverse ARM datasets in articles and other papers. This strategy eases the tracking of data provided as supplements to articles and papers. Additionally, it allows future data users and the ARM Climate Research Facility to easily locate the exact data used in various articles. Traditionally, DOIs are assigned to individual digital objects (a report or a data table), but for ARM datasets, these DOIs are assigned to an ARM data product. This eliminates the need for creating DOIs for numerous components of the ARM data product, in turn making it easier for users to manage and cite the ARM data with fewer DOIs. In addition, the ARM data infrastructure team, with input from scientific users, developed a citation format and an online data citation generation tool for continuous data streams. As a result, this citation format includes DOIs along with additional details such as spatial and temporal information.},

  doi          = {10.3390/data1020011},

  journal      = {Data},

  number       = 2,

  volume       = 1,

  place        = {United States},

  year         = {Wed Aug 31 00:00:00 EDT 2016},

  month        = {Wed Aug 31 00:00:00 EDT 2016}

}

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