1. Data Citation as a Service
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012
2. Background
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
3. Background (overly simplified)
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
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.
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
4. Background (overly simplified)
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
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.
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
5. Data Service Packages
• Planning and collection
• Discovery
• Distribution
• Readability/Reuse
• Archiving
• Visualization
• Interoperability
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
6. But…
• Planning and collection
• Discovery
• Distribution
• Readability/Reuse
• Archiving
• Visualization
• Interoperability
Where does data citation fit?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
7. Approach
Disambiguate
‘Data Citation’
and
‘Data Service’
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
8. Approach
‘Data Citation’
Citation Metadata
Access Mechanism
+
‘Data Service’
Defined Need + User Community
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
9. 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 (?)
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
10. 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)
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
11. Bringing these together…(work in progress!)
Service Packages
User Needs
Data Locator
Planning and collection
Claiming attribution
Discovery Tracking reuse statistics
Distribution Following citations
Readability/Reuse Connect data and resulting
Archiving scholarship
Referencing data used in support
Visualization
of scholarship
Interoperability Supporting reproducibility
Assurance of long-term support
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
12. 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?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
13. 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)
§ …
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
14. 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
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
15. Dependency
What are the Service and User Community
priorities for the organization?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
16. Taking a step back
What are the Service and User Community
priorities for the organization?
Should every service center be meeting every need and/or
offering every service?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
17. Even further
What are the Service and User Community
priorities for the organization?
Should every service center be meeting every need and/or
offering every service?
Might a metadata model be helpful?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
18. Thank You!
Special thanks to:
Mark Parsons, Matt Mayernik, and
the ACADIS team!
Visit ACADIS: aoncadis.org
Visit the Arctic Portal: coming soon!
Contact me: lynn.yarmey@colorado.edu
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo