Bryan Beecher University of Michigan Director, Computing & Network Services E: [email protected]W: http://www.icpsr.umich.edu/ICPSR/staff/beecher. Micah Altman Harvard University Archival Director, Henry A. Murray Research Archive Associate Director, Harvard-MIT Data Center Senior Research Scientist, Institute for Quantitative Social Sciences E: [email protected]W: http://maltman.hmdc.harvard.edu/
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Archival Director, Henry A. Murray Research ArchiveAssociate Director, Harvard-MIT Data CenterSenior Research Scientist, Institute for Quantitative Social SciencesE: [email protected]: http://maltman.hmdc.harvard.edu/
Find diverse partners – diverse business models, legal regimes
http://failblog.org/2008/02/08/floppy-fail/
Consider organizational credentials
No organization is absolutely certain to be reliable
Consider the trust relationships across institutions
http://flickr.com/photos/phauly/35555985/
Policy Driven Institutional policy creates formal
replication commitments Replication commitments are described in
metadata, using schema Metadata drives
Configuration of replication network Auditing of replication network
Asymmetric CommitmentsPartners vary in … … storage commitments to replication … size of holdings being replicated … what holdings of other partners they
replicate
Completeness Complete public holdings of each partner Retain previous version of holdings Include
metadata data documentation legal agreements
Restoration guarantees Restore groups of versioned content
to owning archive to replication hosts
Institutional failure restoration:– transfer entire holdings of an archive to another
Trust & Verification Each partner is trusted …
… to hold the public content of other(not to disseminate improperly) … to add units to be harvested
No partner is trusted to be “super-user” No deletion (or directly manipulation of replication storage owned by another partner
Legal agreements reinforce trust model Schema based auditing used to …
… verify replication guarantees are met … record replication and storage commitments … document related TRAC criteria
point URI Capabilities: protocol version; number of
replicates maintained; replication frequency; versioning/deletion support
Human readable documentation: restrictions on content that may be placed in the network; services guaranteed by the network; Virtual Organization policies relating to network maintenance
Data-PASS customizations for schema processing Translating schema instance into bulk update requests Reporting on compliance based on cache monitor database
Summer 2007: Attended the MetaArchive LOCKSS tutorial Very good overview of LOCKSS
Summer 2007: SSP System Requirements Developed & Approved Winter 2007: First public LOCKSS network nodes built at two Data-PASS sites Winter 2007: SSP Replication Commitment Schema Developed Spring 2008: Completed Test harvest of MRA collection into LOCKSS Sprint 2008: SSP System Use Cases Developed Spring 2008: Prototype plugin developed to harvest Dataverse Networks Spring 2008: Data-PASS sites are joined into single Private LOCKSS Network (PLN) Spring 2008: Met with LOCKSS developers to review use cases
SSP will leverage functionality “in the works” by LOCKSS team
Replication ameliorates institutional risks to preservation
Data PASS requires policy based, auditable, asymmetric replication commitments
Formalize policy in schema (Re)Configure & audit LOCKSS using