ucar data citationworkshop_yarmey_20120405

Data Citation as a Service

Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012

Program Logo Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012

Background

•  Conversation started in the context of defining ‘Levels of Service’ for ACADIS data


Background (overly simplified)


Approach for prescribing services for incoming data sets given the assumption that these data sets do not have the

same needs, resources, and user communities.


Background (overly simplified)


Advanced Cooperative Arctic Data and Information Service – A collaborative (NSIDC, NCAR-CISL, NCAR-EOL, Unidata)

data service project to support the collection, description, distribution, and archiving of NSF-funded Arctic research data.


Data Service Packages

•  Planning and collection •  Discovery •  Distribution •  Readability/Reuse •  Archiving •  Visualization •  Interoperability


But…

•  Planning and collection •  Discovery •  Distribution •  Readability/Reuse •  Archiving •  Visualization •  Interoperability

Where does data citation fit?


Approach

Disambiguate ‘Data Citation’ and ‘Data Service’


Approach

‘Data Citation’

‘Data Service’

Citation Metadata + Access Mechanism

Defined Need + User Community


Defined needs for data citations

•  Data Locator •  Mechanism for professional recognition

§  Claiming attribution

•  Tracking reuse statistics (metrics) •  Following citations (chaining) •  Connect data and resulting scholarship •  Referencing data used in support of scholarship

§  Supporting reproducibility

•  Assurance of long-term support (?)


Generalized User Communities

•  Data Authors/Submitters §  Mechanism for professional recognition §  Connecting data and resulting scholarship §  Following citations (chaining) §  Assurance of long-term support (?)

•  Data Reusers/Downloaders §  Data Locator §  Specifying data used in support of scholarship §  Following citations (chaining)


Bringing these together…(work in progress!)

Planning and collection Discovery Distribution Readability/Reuse Archiving Visualization Interoperability

Service Packages User Needs Data Locator Claiming attribution Tracking reuse statistics Following citations Connect data and resulting

scholarship Referencing data used in support

of scholarship Supporting reproducibility Assurance of long-term support


Implications

•  Where in the data workflow citation/persistent identifier are applied

•  The granularity of citation application •  The object defined for persistent identification •  Workflow for citation assignment •  Roles

§  What is the role of the PI/data author? §  What are the roles and responsibilities for data service

groups? o  What expertise is required to fulfill these?


Short-term steps for ACADIS

•  Collect citation metadata •  Enact data versioning •  Distinguish citation recommendations and assignment

§  We can recommend citations for all data sets (we have the metadata!)

§  But we will only assign citations to data sets with data submitted (proposed)

§  …


Short-term steps for ACADIS

•  … •  Separate application of citations vs. identifiers

§  Citations applied to all submitted data sets and not to metadata-only data sets

§  Persistent identifiers applied to approved data sets (AKA: “roughly stable,” “good” data sets)

•  Be clear about this with data submitters and users


Dependency

What are the Service and User Community priorities for the organization?


Taking a step back


Should every service center be meeting every need and/or offering every service?


Even further


Should every service center be meeting every need and/or offering every service?

Might a metadata model be helpful?


Thank You!

Visit ACADIS: aoncadis.org Visit the Arctic Portal: coming soon!

Contact me: [email protected]

Special thanks to: Mark Parsons, Matt Mayernik, and the ACADIS team!

ucar data citationworkshop_yarmey_20120405

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