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Data-PASS: How Collaborative Presentation Works

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Presented at IASSIST 2010, Ithaca

Presented at IASSIST 2010, Ithaca

Published in: Education, Technology

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    • 1. Data-PASS:How collaborative preservation worksMicah Altman, Harvard UniversityIASSIST 2010, Ithaca New York 1
    • 2. What’s next? ✤ What is Data-PASS? ✤ Challenges of preserving scientiﬁc evidence ✤ Converging trends ✤ Beneﬁts of institutional collaboration ✤ Evolving structure of collaboration ✤ Services and infrastructure 2How collaborative preservation works.
    • 3. Collaborators and Co-Conspirators ✤ Margaret Adams, Caroline Arms, Ed Bachman, Nitin Borwankar, Adam Buchbinder, Ken Bollen, Bryan Beecher, Steve Burling, Jonathan Crabtree, Darrell Donakowski, Myron Gutmann, Gary King, Patrick King, Jared Lyle, Marc Maynard, Amy Pienta, Lois Timms-Ferrarra, Copeland Young. ✤ Research Support Thanks to the Library of Congress (PA#NDP03-1), the National Science Foundation (DMS-0835500, SES 0112072), IMLS (LG-05-09-0041-09), the Harvard University Library, the Institute for Quantitative Social Science, the Harvard-MIT Data Center, and the Murray Research Archive. 3How collaborative preservation works.
    • 4. What is Data-PASS? ✤ Data-PASS is a broad-based partnership of data archives dedicated to acquiring and preserving data at- risk of being lost to the social science research community. ✤ Data-PASS partners have rescued thousands of data sets and created the largest catalog of social science data in existence. ✤ Data-PASS partners collaborate to ✤ identify and promote good archival practices, ✤ seek out at-risk research data, ✤ build preservation infrastructure, ✤ and mutually safeguard collections. ✤ Our current initiatives include: ✤ improving data citation practices, ✤ automatic policy-based archival replication 4How collaborative preservation works.
    • 5. Challenges of Preserving Scientific Evidence✤ Scientists expectations are changing ✤ Movements toward open access and open data ✤ Specialized workﬂow systems ✤ Diversity of approaches to managing replication and community data✤ Scientiﬁc change creates technical challenges: ✤ Forms, formats, and research workﬂows change ✤ Data is not self-documenting ✤ Intellectual property & privacy law are evolving ✤ Resources to deal with these changes are limited✤ Much of the empirical base of science becomes lost Source: Wikimedia Commons ✤ Journal articles & books are only summaries ✤ Full replication is expensive or impossible ✤ This slows scientiﬁc progress: cooked results, publication bias, citation authority distortion, challenges of meta- analysis 5How collaborative preservation works.
    • 6. Converging trends in preservation ✤ Standardized criteria for evaluating trustworthiness of archives ✤ TRAC; NARA TDR; Drambora ✤ Collaborative stewardship by memory institutions ✤ Meta-Archive, CLOCKSS, COPUL, PeDALS, ADN, Chronopolis ✤ Technology for replication and veriﬁcation ✤ Solutions developed within the library/archival community: LOCKSS, IRODS, ACE, Duraspace ✤ Commercial HPC and Cloud solutions: Hadoop, Crashplan, Mozy, AWS, etc. ✤ P2P sharing: freenet, gnunet, Taho-LAFS 6How collaborative preservation works.
    • 7. Benefits of Collaboration "Nothing new that is really interesting comes without collaboration" -- James Watson ✤ General Benefits ✤ Exposure to funding opportunities; collection development leads ✤ Division of labor in tracking law, technology, information science ✤ Combined experience in preservation practice ✤ Data-PASS Focus* ✤ Expanded discoverability of collections ✤ Reach new audiences ✤ Holdings across the joint collection are more complete ✤ Virtual collections can be built from slices of the joint collection ✤ Development and advocacy of archival good practices ✤ (Current initiative: outreach to professional associations in support of data citation) ✤ Insurance against institutional and technological failure 7How collaborative preservation works. * And the museum of obsolete data storage technologies
    • 8. How Collaborative Stewardship acts as Insurance Against Preservation Failure ✤ Collaborative replication & stewardship can substantially mitigate preservation risk from: ✤ External threats to institution failure: ✤ funding loss; attacks; legal regime change; mission drift ✤ Institutional failure: ✤ Unintentional curatorial modiﬁcation; Loss of institutional knowledge; Change in mission ✤ And also reduce preservation risk from: ✤ Media failure (from storage & media characteristics); Software & hardware infrastructure failures 8How collaborative preservation works.
    • 9. Shared Infrastructure ✤ Shared infrastructure can ✤ reduce costs ✤ reduce risk ✤ coordinate operations ✤ validate shared standards ✤ Data-PASS Shared Infrastructure ✤ Shared Catalog ✤ Policy-Driven Distributed Replication (in development) ✤ The Dataverse Network (overlapping infrastructure) 9How collaborative preservation works.
    • 10. Shared Catalog ✤ Uniﬁed Discovery ✤ Simple & ﬁelded search ✤ Virtual collection across entire catalog ✤ Browse by subject, data, source ✤ Metadata delivery ✤ Descriptive study, ﬁle, and variable information ✤ Provenance & rights metadata ✤ Human, OAI, Z39.50 interfaces ✤ Layered Services ✤ Data reformatting for delivery ✤ On-line analysis 10How collaborative preservation works.
    • 11. The Dataverse Network ® For Organizations For Scholars✤ Dataverses are Data-PASS ready -- all dataverses can provide: ✤ The Dataverse Network System is Open-Source and ✤ DDI (2.x) metadata export (intuitive form-based entry) ✤ Creating a Dataverse requires no software. ✤ Catalog access through OAI-PMH (and Z39.50) ✤ IQSS & MRA host an open DVN and offer no-cost ✤ LOCKSS compatibility permanent storage: ✤ Version control (new); Terms of use metadata; Flexible http://dvn.iq.harvard.edu contributor-curator-editor workﬂows 11How collaborative preservation works. (better) self-archiving -- ideal for “living collections” &
    • 12. Policy-Driven Distributed Replication ✤ Policy Based ✤ Preservation requirements shape policy ✤ Policy drives replication rules ✤ Auditing demonstrates conformance with preservation requirements ✤ Copies are distributed ✤ Across space ✤ Among institutions ✤ Across time (version history retained) ✤ Commitments scaled to participant resources ✤ Collection size ✤ Technology 12How collaborative preservation works.
    • 13. Structure of CollaborationAreas of collaboration... Steps to participation ✤ Partnership agreements Partners agree to... agreement on good practice; ✤ Publishing metadata permission to preserve; partners offer to accept data transfer if archive fails ✤ Use of replication system ✤ Coordinated operations ✤ Good archival practice (TRAC compliance not required) shared leads; regular communication; ✤ Transfer protocols collegial review available Partners use the following technlogies ✤ Shared good practice ✤ Light-weight protocols: OAI-PMH + DDI 2-lite + metadata; preservation; conﬁdentiality HTTP harvestable data ✤ Circle of gifts norm ✤ Software: Could use a hosted dataverse or; in-kind effort & resource; install open source OAI-PMH server, etc. contributions are voluntary & proportional ✤ No fear - we can help! 13
    • 14. More Questions? ✤ Know of research data at risk of loss? ✤ Need help preserving your research data? ✤ Want more visibility and protection for your collections ? http://data-pass.org data-pass@icpsr.umich.edu 14How collaborative preservation works.
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