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IDCC 2016 Dash Presentation

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Dash: Data Sharing Made Easy at the University of California
The new Stash platform is intended to enhance the existing Dash service by providing individual researchers the self-service ability to:
Preserve, manage and share datasets by uploading to appropriate & existing content repositories
Select datasets for deposit by means of local file browse or drag-and-drop operations
Discover, retrieve and re-use datasets by means of the faceted search / browse of an aggregated data corpus
Prepare datasets for deposit by reviewing best practice guidance for the creation or acquisition of research data
Follow incoming links (from paper references, catalogs, web searches, etc.) to dataset landing pages.

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IDCC 2016 Dash Presentation

  1. 1. DASH: Making Data Sharing Easier Marisa Strong University of California Cura;on Center (UC3)
  2. 2. California Digital Library – University of California Cura;on Center
  3. 3. Research Lifecycle
  4. 4. Dash helps researchers in six ways: • Prepare • Select • Describe • Iden1fy • Preserve • Discover
  5. 5. Prepare
  6. 6. Select
  7. 7. Describe
  8. 8. Describe
  9. 9. Iden;fy
  10. 10. Preserve
  11. 11. Discover
  12. 12. Fully Pluggable Stash platform Harvest Share Store Dash portal Standards-compliant repository SWORD SWORD EZID DataCite ORCID Fundref IdP SWORD OAI-PMH Index
  13. 13. Standards-based •  Metadata Modules •  Harves;ng protocols •  Deposi;ng protocols •  Authen;ca;on protocols Plus, integra;on with Fundref and ORCID And, op;mized for accessibility and mobile
  14. 14. Open Source •  Ruby on Rails app •  MapZen for GeoNames •  GeoBlacklight/SOLR for search •  hUp://cdluc3.github.io/dash/ •  New version launch date: April 2016
  15. 15. Dash for the community •  More informa;on @UC3dash •  dash.cdlib.org Contact: marisa.strong@ucop.edu

Dash: Data Sharing Made Easy at the University of California The new Stash platform is intended to enhance the existing Dash service by providing individual researchers the self-service ability to: Preserve, manage and share datasets by uploading to appropriate & existing content repositories Select datasets for deposit by means of local file browse or drag-and-drop operations Discover, retrieve and re-use datasets by means of the faceted search / browse of an aggregated data corpus Prepare datasets for deposit by reviewing best practice guidance for the creation or acquisition of research data Follow incoming links (from paper references, catalogs, web searches, etc.) to dataset landing pages.

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