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air • planet • people Integrated Information Services (IIS) UCAR NCAR UCP

Digital Resource Attribution and Citation through Unique Identifiers

Matt Mayernik Project Scientist

Research Data Services Specialist NCAR Library/Integrated Information Services (IIS)

DCERC Kickoff Workshop June, 2014


NCAR/UCAR Community Resources

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Issues

• Discoverability - How to get UCAR resources in the hands of researchers and students? – Finding data on the internet can be very difficult – Most data are discovered through the literature

• Traceability - How to connect scholarship with underlying resources? – Reproducibility and transparency of science – Digital resources are largely linkable online

• Attribution - How to reward production of digital resources, e.g. data and software? – Data/software production, management, and support require significant

expertise and effort – Professional credit structures rarely account for this work

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5th Coupled Model Intercomparison Project (CMIP5)

“Previous archives have not always been careful about version control ..., and it has not always been clear which data has eventually been used. In the case of CMIP3 and AR4 an additional problem has been that it was not clear which data was in the CMIP3 archive at any time, and so in some cases where users have used ‘all the CMIP3 models’ or ‘all the AR4 models’ it is non-trivial to go back and be sure what data has been used.”

– Williams, D. N., Lawrence, B. N., Lautenschlager, M., Middleton, D., & Balaji, V. (2011). The Earth System Grid Federation: Delivering globally accessible petascale data for CMIP5. In Proceedings of the 32nd Asia-Pacific Advanced Network Meeting., 121-130. Quote from pg. 125. http://home.badc.rl.ac.uk/lawrence/static/2012/02/15/WilEA11.pdf

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What is a Data Citation?

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Example from: Lindsay, R., et al. 2012. Seasonal forecasts of Arctic sea ice initialized with observations of ice thickness. Geophysical Research Letters, 39(21). DOI: 10.1029/2012GL053576

Citation to journal article

Citation to data set


Data Citation Recommendations

• Earth Science Information Partners (US): http://bit.ly/data_citation

• Digital Curation Centre (UK): http://www.dcc.ac.uk/resources/how-guides/cite-datasets

• Joint Declaration of Data Citation Principles (Feb 2014): http://www.force11.org/datacitation – 60 organizational endorsements to date

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Challenge – Overcoming Inertia • Researchers may not…

– know that they are asked to cite data – know how to cite data – know that they have data to cite – be willing to spend time creating data citations

• Data users typically acknowledge their data sets and software using some combination of: – In-text descriptions of data sets and/or data providers – Mentions in the acknowledgements sections of a paper – Citations to papers about a data set – Including data set collectors/creators as coauthors on the paper

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Challenge – Data ≠ Article • Digital resources are highly heterogeneous and dynamic

– At what granularity should digital identifiers be assigned? – How should identifiers be assigned to resources that change over

time? • Who “owns” digital identifiers in multi-organizational projects? • Data “peer review” is not yet a well specified process

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UCAR Data Citation Initiatives

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• Develop coherent approaches across the organization for: – Technical tools and methods – Policy/procedural protocols and standards – User and community engagement

• Broad participation from UCAR/NCAR groups – CISL/DSS, CISL/VETS, EOL, IIS, NESL/CGD, Unidata

• Engagement with other groups – CISL/IMAGe, CISL/USS, HAO, JOSS, RAL, NESL/ACD


Actionable Identifiers

• Assigning actionable identifiers to digital resources – Digital Object Identifiers (DOIs)

• Provide a persistent locator for internet-based resources • Widely used for scholarly papers • Growing use for other kinds of resources

– Archival Resource Keys (ARKs) • Less implication of persistence • Additional features to address granularity

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Data http://dx.doi.org/10.5065/D6RN35ST

resolves to http://www.earthsystemgrid.org/project/NARCCAP.html

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http://www.earthsystemgrid.org/project/NARCCAP.html�

Software http://dx.doi.org/10.5065/D6WD3XH5 resolves to

http://www.ncl.ucar.edu/

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http://www.ncl.ucar.edu/�

Facilities / Services http://n2t.net/ark:/85065/d7wd3xhc resolves to

http://www2.cisl.ucar.edu/resources/yellowstone

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http://www2.cisl.ucar.edu/resources/yellowstone�

Citations

• NARCCAP Data: – Mearns, L.O., et al., 2007, updated 2012. The North American Regional

Climate Change Assessment Program dataset, National Center for Atmospheric Research Earth System Grid data portal, Boulder, CO. Data downloaded 2014-05-22. [doi:10.5065/D6RN35ST]

• NCL Software: – The NCAR Command Language (Version 6.1.2) [Software]. (2013).

Boulder, Colorado: UCAR/NCAR/CISL/VETS. http://dx.doi.org/10.5065/D6WD3XH5

• Yellowstone Supercomputer: – Computational and Information Systems Laboratory. 2012.

Yellowstone: IBM iDataPlex System (Climate Simulation Laboratory). Boulder, CO: National Center for Atmospheric Research. http://n2t.net/ark:/85065/d7wd3xhc

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http://dx.doi.org/10.5065/D6RN35ST�

http://dx.doi.org/10.5065/D6WD3XH5�

http://n2t.net/ark:/85065/d7wd3xhc�

User Services

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UCAR/NCAR Progress

• Community and consensus building • Producing technical reports

– White paper on internal identifier and citation recommendations – Report from UCAR data citation workshop held in 2012

• Organizing citation implementations within individual groups – UCAR groups have assigned citable identifiers to 38 data sets,

2 software packages, 1 model, and 1 facility – NCAR Library has assigned citable identifiers to 550+ NCAR

Technical Notes and UCAR Manuscripts

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Early Metrics

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Citations and acknowledgements to UCAR resources using unique digital identifiers

ID Resource UCAR Group Date of ID

Assignment Citations Acknow. Both TOTAL

10.5065/D6WD3XH5 NCL Software CISL VETS April 2012 29 25 54

10.5065/D6RN35ST NARCCAP Data CISL May 2012 16 16 85065/d7wd3xhc (ARK) Yellowstone supercomputer CISL May 2012 3 18 3 24

10.5065/D6CC0XMC Barrow Airborne Sea Ice

Data ACADIS Sept. 2012 1 1

10.5065/D6FF3QBR NCAR Tech Note - APE Atlas NCAR Library Feb. 2013 7 7

10.5065/D6NZ85N3 Juneau Icefield Glacier Mass

Balance ACADIS April 2013 1 1

10.5065/D6DF6P6C

Marine Regions Boundary Data for the Bering Sea Shelf

and Slope EOL May 2013 3 3

10.5065/D6N014HK USGS Permafrost data ACADIS Oct. 2013 1 1

Table compiled by querying IDs in Google Scholar, Apr. 10, 2014

Professional Societies

• American Meteorological Society – Policy Statement on “Full and Open Access to Data” officially adopted

by AMS in Dec. 2013. http://www.ametsoc.org/policy/2013fullopenaccessdata_amsstatement.html

– Data citation recommendations put forth to AMS Publications Commission in April 2014. Currently under consideration.

1. Add data citation to the author guidelines 2. Add data citation to the reviewer guidelines 3. Encourage authors to consider data requirements early

• American Geophysical Union – New Publications Data policy as of Dec. 2013 – “…all data necessary to understand, evaluate, replicate, and build

upon the reported research must be made available and accessible whenever possible.”

http://publications.agu.org/author-resource-center/publication-policies/data-policy/

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Integrating Citation Tools and Repositories

• New tools for software archiving and citation - DOIs for GitHub software repositories – Integrating with the Zenodo data repository – Zenodo makes an archive copy for every code “release”

https://guides.github.com/activities/citable-code/

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Going Forward

• Need to embed digital resource citation within research institutions – Norms of practice and symbols of success and importance – Intermediaries who provide assistance and expertise – Routines for making citations very easy to find, create, and use – Standards should be endorsed and used – Embedding within stable long-term archives and repositories is

essential

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Thank You

NCAR Technical Notes: – “Data Citations in NCAR” - http://dx.doi.org/10.5065/D6ZC80VN – “Bridging Data Lifecycles: Tracking Data Use via Data Citations

Workshop Report” - http://dx.doi.org/10.5065/D6PZ56TX Forthcoming article: – Mayernik, M.S., Callaghan, S., Leigh, R., Tedds, J., & Worley, S.

(in press). Peer review of data sets: When, why, and how. Bulletin of the American Meteorological Society. http://dx.doi.org/10.1175/BAMS-D-13-00083.1

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