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Data 2016, 1(2), 11; doi:10.3390/data1020011

Data Always Getting Bigger—A Scalable DOI Architecture for Big and Expanding Scientific Data

1
Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831, USA
2
Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA 99354, USA
3
DOE Office of Scientific and Technical Information, 1 Science.gov Way, Oak Ridge, TN 37830, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Jamal Jokar Arsanjani
Received: 24 March 2016 / Revised: 19 July 2016 / Accepted: 9 August 2016 / Published: 31 August 2016
View Full-Text   |   Download PDF [4582 KB, uploaded 31 August 2016]   |  

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. This citation format includes DOIs along with additional details such as spatial and temporal information. View Full-Text
Keywords: Atmospheric Radiation Measurement; DOIs; Digital Object Identifier; data citation; arm data citation; continuous data citation Atmospheric Radiation Measurement; DOIs; Digital Object Identifier; data citation; arm data citation; continuous data citation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Prakash, G.; Shrestha, B.; Younkin, K.; Jundt, R.; Martin, M.; Elliott, J. Data Always Getting Bigger—A Scalable DOI Architecture for Big and Expanding Scientific Data. Data 2016, 1, 11.

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