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Enabling the Preservation Relay: Interoperable
Repository Architectures
J O N W H E E L E R J W H E E L 0 1 @ U N M . E D U
K A R L B E N E D I C T K B E N E @ U N M . E D U
U N I V E RS I T Y O F N E W M E X I C O
C O L L E G E O F U N I V E R S I T Y L I B R A R I E S A N D L E A R N I N G S C I E N C E S
Background
Data Management and Institutional Repository Service Drivers
◦ Data repositories as stakeholders in contrast with individuals as stakeholders
◦ Collections in contrast with individual items
◦ How do we add value (or maintain added value) to previously published
data?
Scope, Cost, and Service Models
◦ Organizational priorities & sustainability
◦ Complementary roles for institutional and data repositories
Repository Ecosystem
Repository Ecosystem
Repository Ecosystem
Case Study: GSToRE
Geographic Storage, Transformation, and Retrieval Engine
◦ Part of the US National Spatial Data Infrastructure (NSDI)
◦ Underlying platform for the NM Resource Geographic Information System
(NM RGIS), the NM NSF EPSCoR Program’s Data Portal, and the data hub for
a second multi-state NSF EPSCoR environmental modeling project
Requirements & Capabilities
◦ Integration with external discovery and access services
◦ Support for diverse geospatial and non-geospatial data types
◦ Standards based, tiered RESTful Services Oriented Architecture (SOA)
No Explicit Focus on Long-term Archival Storage
• Emphasis on value-added services
• Data management best practices
GSToRE Data Model
GSToRE Replication and
Repository API
Initial experimentation with harvest via standard search, metadata and
data retrieval API (production services)
◦ Enables search and retrieval of data and metadata elements for all data in
GSToRE
◦ Processed GSToRE items not identified by GSToRE
Experimental Repository API
◦ Enables “flagging” of individual data objects in GSToRE as harvest targets for
one or more repositories – e.g. Data.gov, DataONE,
LoboVault/DigitalRepository.unm.edu
◦ Enables explicit specification of harvest intention by GSToRE
◦ Intended as an interface for middleware processes
Overview of a Migration
Source Repositories as Stakeholders
◦ Communication, roles, and responsibilities
◦ Copyright, use, and access requirements
Collections and Items
◦ Which data to transfer?
◦ Metadata requirements
◦ Collection & Disciplinary context
◦ Repository context
◦ Item context
◦ Content and format requirements
Evolving the Conceptual Model into Practical Strategies
◦ Revisiting the GSToRE harvest prototype for Sevilleta LTER data
Harvest
Curation & Packaging
Bibliography
1. Baker, Karen S, and Florence Millerand. “Infrastructuring Ecology: Challenges in Achieving Data Sharing.” Collaboration in the New Life Sciences. Ashgate.(To Be Published in
2010), 2010.
2. Baker, Karen S., and Lynn Yarmey. “Data Stewardship: Environmental Data Curation and a Web-of-Repositories.” International Journal of Digital Curation 4, no. 2 (October 15,
2009): 12–27. doi:10.2218/ijdc.v4i2.90.
3. “Certification and Assessment of Digital Repositories | CRL.” Accessed December 5, 2016. https://www.crl.edu/archiving-preservation/digital-archives/certification-assessment.
4. Consultative Committee for Space Data Systems. “Recommended Standard for Producer-Archive Interface Specification (PAIS),” February 2014.
https://public.ccsds.org/Pubs/651x1b1.pdf.
5. ———. “Reference Model for an Open Archival Information System (OAIS), Recommended Practice,” 2012.
6. Conway, Esther, David Giaretta, Simon Lambert, and Brian Matthews. “Curating Scientific Research Data for the Long Term: A Preservation Analysis Method in Context.”
International Journal of Digital Curation 6, no. 2 (2011): 38–52.
7. Conway, Esther, Brian Matthews, David Giaretta, Simon Lambert, Michael Wilson, and Nick Draper. “Managing Risks in the Preservation of Research Data with Preservation
Networks.” International Journal of Digital Curation 7, no. 1 (March 12, 2012): 3–15. doi:10.2218/ijdc.v7i1.210.
8. “Data Seal of Approval Management.” Accessed December 5, 2016. https://assessment.datasealofapproval.org/.
9. Janée, Greg, Justin Mathena, and James Frew. “A Data Model and Architecture for Long-Term Preservation.” In Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital
Libraries, 134–144. ACM, 2008.
10. Key Perspectives Ltd. “Data Dimensions: Disciplinary Differences in Research Data Sharing, Reuse and Long Term Viability. SCARP Synthesis Study.” Digital Curation Center, 2010.
http://hdl.handle.net/1842/3364
11. Ray, Joyce M. Research Data Management: Practical Strategies for Information Professionals. West Lafayette, Indiana: Purdue University Press, 2014.
12. “re3data.org | Registry of Research Data Repositories.” Accessed December 6, 2016. http://www.re3data.org/.
13. Treloar, Andrew, David Groenewegen, and Cathrine Harboe-Ree. “The Data Curation Continuum: Managing Data Objects in Institutional Repositories.” D-Lib Magazine 13, no. 9
(2007): 4.

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Wheeler & Benedict -- Enabling the Preservation Relay

  • 1. Enabling the Preservation Relay: Interoperable Repository Architectures J O N W H E E L E R J W H E E L 0 1 @ U N M . E D U K A R L B E N E D I C T K B E N E @ U N M . E D U U N I V E RS I T Y O F N E W M E X I C O C O L L E G E O F U N I V E R S I T Y L I B R A R I E S A N D L E A R N I N G S C I E N C E S
  • 2. Background Data Management and Institutional Repository Service Drivers ◦ Data repositories as stakeholders in contrast with individuals as stakeholders ◦ Collections in contrast with individual items ◦ How do we add value (or maintain added value) to previously published data? Scope, Cost, and Service Models ◦ Organizational priorities & sustainability ◦ Complementary roles for institutional and data repositories
  • 6. Case Study: GSToRE Geographic Storage, Transformation, and Retrieval Engine ◦ Part of the US National Spatial Data Infrastructure (NSDI) ◦ Underlying platform for the NM Resource Geographic Information System (NM RGIS), the NM NSF EPSCoR Program’s Data Portal, and the data hub for a second multi-state NSF EPSCoR environmental modeling project Requirements & Capabilities ◦ Integration with external discovery and access services ◦ Support for diverse geospatial and non-geospatial data types ◦ Standards based, tiered RESTful Services Oriented Architecture (SOA) No Explicit Focus on Long-term Archival Storage • Emphasis on value-added services • Data management best practices
  • 8. GSToRE Replication and Repository API Initial experimentation with harvest via standard search, metadata and data retrieval API (production services) ◦ Enables search and retrieval of data and metadata elements for all data in GSToRE ◦ Processed GSToRE items not identified by GSToRE Experimental Repository API ◦ Enables “flagging” of individual data objects in GSToRE as harvest targets for one or more repositories – e.g. Data.gov, DataONE, LoboVault/DigitalRepository.unm.edu ◦ Enables explicit specification of harvest intention by GSToRE ◦ Intended as an interface for middleware processes
  • 9. Overview of a Migration Source Repositories as Stakeholders ◦ Communication, roles, and responsibilities ◦ Copyright, use, and access requirements Collections and Items ◦ Which data to transfer? ◦ Metadata requirements ◦ Collection & Disciplinary context ◦ Repository context ◦ Item context ◦ Content and format requirements Evolving the Conceptual Model into Practical Strategies ◦ Revisiting the GSToRE harvest prototype for Sevilleta LTER data
  • 12. Bibliography 1. Baker, Karen S, and Florence Millerand. “Infrastructuring Ecology: Challenges in Achieving Data Sharing.” Collaboration in the New Life Sciences. Ashgate.(To Be Published in 2010), 2010. 2. Baker, Karen S., and Lynn Yarmey. “Data Stewardship: Environmental Data Curation and a Web-of-Repositories.” International Journal of Digital Curation 4, no. 2 (October 15, 2009): 12–27. doi:10.2218/ijdc.v4i2.90. 3. “Certification and Assessment of Digital Repositories | CRL.” Accessed December 5, 2016. https://www.crl.edu/archiving-preservation/digital-archives/certification-assessment. 4. Consultative Committee for Space Data Systems. “Recommended Standard for Producer-Archive Interface Specification (PAIS),” February 2014. https://public.ccsds.org/Pubs/651x1b1.pdf. 5. ———. “Reference Model for an Open Archival Information System (OAIS), Recommended Practice,” 2012. 6. Conway, Esther, David Giaretta, Simon Lambert, and Brian Matthews. “Curating Scientific Research Data for the Long Term: A Preservation Analysis Method in Context.” International Journal of Digital Curation 6, no. 2 (2011): 38–52. 7. Conway, Esther, Brian Matthews, David Giaretta, Simon Lambert, Michael Wilson, and Nick Draper. “Managing Risks in the Preservation of Research Data with Preservation Networks.” International Journal of Digital Curation 7, no. 1 (March 12, 2012): 3–15. doi:10.2218/ijdc.v7i1.210. 8. “Data Seal of Approval Management.” Accessed December 5, 2016. https://assessment.datasealofapproval.org/. 9. Janée, Greg, Justin Mathena, and James Frew. “A Data Model and Architecture for Long-Term Preservation.” In Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries, 134–144. ACM, 2008. 10. Key Perspectives Ltd. “Data Dimensions: Disciplinary Differences in Research Data Sharing, Reuse and Long Term Viability. SCARP Synthesis Study.” Digital Curation Center, 2010. http://hdl.handle.net/1842/3364 11. Ray, Joyce M. Research Data Management: Practical Strategies for Information Professionals. West Lafayette, Indiana: Purdue University Press, 2014. 12. “re3data.org | Registry of Research Data Repositories.” Accessed December 6, 2016. http://www.re3data.org/. 13. Treloar, Andrew, David Groenewegen, and Cathrine Harboe-Ree. “The Data Curation Continuum: Managing Data Objects in Institutional Repositories.” D-Lib Magazine 13, no. 9 (2007): 4.