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The Alliance for Data Archive Technologies: Looking towards a Common Future

The Alliance for Data Archive Technologies: Looking towards a Common Future. Myron Gutmann, ICPSR Ben Evans, ASSDA Deborah Mitchell, ASSDA Kevin Schürer, UK Data Archive. Overview. Why? What? Why Now? Early Steps Understanding Process Understanding Needs Next Steps. Why?.

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The Alliance for Data Archive Technologies: Looking towards a Common Future

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  1. The Alliance for Data Archive Technologies: Looking towards a Common Future Myron Gutmann, ICPSR Ben Evans, ASSDA Deborah Mitchell, ASSDA Kevin Schürer, UK Data Archive

  2. Overview • Why? • What? • Why Now? • Early Steps • Understanding Process • Understanding Needs • Next Steps

  3. Why? • Data curation has been an ad hoc process, with local practices & expertise • Since the 1990s • Enormous investment in technology • Significant successes in social science(SDA, Nesstar, DVN, IPUMS, even ICPSR) • Major new ways to find & use content (Google) & architectures to deliver content (web services)

  4. More Why • Proprietary systems unsustainable • Market too small for commercial systems • Partnerships will help avoid unnecessary duplication of effort & assure efficiency • Need to be truly global

  5. What? • New organization to support technologies for curation, preservation, & delivery that are: • Open • Community-developed • Standards-based • Built on existing networks of social science data archives & technology centers, and … • Open to all who want to contribute

  6. Why Now? Three Standards • DDI – Metadata Standard • OAIS – Preservation Reference Model • Repository Architecture Standards: - Fedora, D-Space & Duraspace • Organizational models like the DDI Alliance, CESSDA, Data-PASS (even the new Hathi Trust)

  7. Why Now? Community Tech • Community-developed software has become widely used • Examples: Drupal/Plone • Examples: Fedora • Examples: SOLR/Lucene • But we shouldn’t ignore all the challenges that this software has faced

  8. Why Now? Workflows • Improved workflow technologies are operating in many of our institutions • Some are shared in CESSDA & Data-PASS • And in other communities: Virtual Observatory • Another challenge: not the same as sharing business practices in complex organizations

  9. Why Now? Progress So Far • SDA • Nesstar • DVN • All used in more than one archive • Not all open-source • Potential shared technologies that we can leverage in the future

  10. 1st Steps: October 2008 Meeting • ICPSR • ASSDA • UKDA • Roper Center - UConn • Odum Ins. – N. Carolina • Harvard - IQSS • Minnesota Pop. Center • Berkeley – SDA • DANS – Netherlands • DDA Denmark • Gesis – ZA • South Africa • DDI Alliance • IASSIST • Library of Congress • U.S. NSF • U.S. NIH • Canadian SSHRC ***Thanks to Library of Congress for hosting

  11. 1st Steps: After October, 2008 • Solicit needs in the form of wish lists • Authorize creation of an organization at an appropriate time • Work on raising money and finding common ground for future work

  12. Process: Begin with OAIS Model

  13. Design OAIS for ICPSR

  14. Focus on Ingest

  15. ICPSR: Standards Compliance OAIS Workflow DDI Workflow Tools for full variable-level metadata creation not dependent on proprietary software (such as SPSS) DDI Editor DDI Converter DDI 2 to 3 translator • Ingest tools • AIP Creation-Validation • SIP Creation-Validation • DIP Creation-Validation • Audit tools

  16. Needs: Wish Lists from … • ICPSR • UKDA • ASSDA • Harvard • Roper Center • Odum Institute • DANS (Netherlands) • DDA (Denmark) • GESIS (Germany) • NSD (Norway) • Minnesota Pop. Center

  17. Needs: A Catalog Administration • Identity management • OAIS workflow & audit (SIP/AIP/DIP) Access • Data format conversion • Setup file creation • International data sharing • Community data/User comments/Web 2.0 • Search • Confidentiality • Persistent identifiers • Visualization • Data citation • Semantic data access • Security Production Data Management • Data producer tools • Open metadata curation • Data format curation • Data management & analysis • Qualitative data management • Data integration • Metadata registries • Survey question management • Data citation Ingest • Open metadata curation • Confidentiality • Software/algorithm archiving Archival Storage • Storage fabric/architecture (FEDORA or ?) • Replication (LOCKSS) • Persistent identifiers • Content model development

  18. Next Steps: Canberra Meeting • Prime Goal: Strategic Planning • What’s the business model? • What are the links to… • Standards? • Security? • Archiving practice & workflows? • Training & Research? • How do we measure success?

  19. Three Major Outcomes • Goal 1: A few critical decisions • Standards, repository framework, software approaches • Goal 2: Initial Common Interests. Examples: • Fedora data/content models • Open source metadata tools (DDI 3?) • Goal 3: How do we collaborate?

  20. Thank you! gutmann@umich.edu deborah.mitchell@anu.edu.au schurer@essex.ac.uk ben.evans@anu.edu.au

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