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Using DSpace as a Disciplinary Data Repository

Using DSpace as a Disciplinary Data Repository. Ryan Scherle National Evolutionary Synthesis Center. NESCent’s Mission. Support synthetic research Develop informatics tools Increase public understanding of science Promote a culture of data sharing. A Repository of Data

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Using DSpace as a Disciplinary Data Repository

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  1. Using DSpace as aDisciplinary Data Repository Ryan Scherle National Evolutionary Synthesis Center

  2. NESCent’s Mission Support synthetic research Develop informatics tools Increase public understanding of science Promote a culture of data sharing

  3. A Repository of Data Underlying Journal Articles

  4. Dryad Partners

  5. Databases in Biology GenBank MorphBank Morphobank PaleoDB Phylota Protein Data Bank TreeBASE Tree of Life AntWeb FishBase FlyBase HerpNet MaNIS ORNIS WormBase ZFIN

  6. The Goal Store all data underlying publications in evolutionary biology, ecology, and related disciplines, at the time of publication. ccaattggct gttcttcgat tctggcgagt GenBank TreeBASE Dryad

  7. (Riju et al., 2007) hdl:10255/dryad.158

  8. (Payne et al., 2008) hdl:10255/dryad.222

  9. (Sidlauskas 2007) hdl:10255/dryad.23

  10. (Taylor and Naish 2007) hdl:10255/dryad.31

  11. (Price et al., 2004) hdl:10255/dryad.82

  12. Deposit at time of publication Repeatability Embargo Exceptions Coordination Joint Data Archiving Policy

  13. Why DSpace? Aren’t data objects usually stored in Fedora? User registration Submission system Administrative interface Search/browse system Manakin Speed of initial implementation

  14. Disciplinary repositories Don’t serve the needs of a single institution Lack a formal organization No formal structure The repository is the “organization” Must locate pockets of dedicated users Must integrate with other community resources

  15. Data repositories Customized metadata fields are required Data often lacks complete metadata Publications can provide context Data comes in a wide variety of formats Connections to other data are valuable

  16. (screenshot – submission summary page)

  17. Submission system

  18. What’s next? OAI harvesting Versioning Authority control Ontology integration Curation interface Faceted search Replication services Tagging, annotation Integration with more journals Integration with partner repositories More submission enhancements Data-specific analysis tools

  19. To learn more… Repository: http://datadryad.org Project info: http://datadryad.org/wiki Source code: http://dryad.googlecode.com

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