Datashare cni spring2013
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A presentation given at the Coalition for Networked Information describing efforts undertaken by 3 partnered organizations (UCSF CTSI, UCSF Library, California Digital Library) to support sharing of research data by UCSF investigators
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Datashare cni spring2013
- 1. DataShare: Collaboration Yields Promising Tool Julia Kochi, UCSF Library Angela Rizk-Jackson, UCSF CTSI Perry Willett, California Digital Library CNI 2013 Meeting San Antonio, TX
- 2. The Background Julia Kochi UCSF Library
- 3. What is DataShare? An open data repository for the UCSF researcher A concept initially envisioned by Michael Weiner, M.D. A collaboration between UCSF CTSI, UCSF Library, and the California Digital Library
- 4. The Problem Increasing requirements to share data • NIH grants >$500k • Publisher requirements Unequal availability of national repositories Campus priorities FASTR, White House Directive
- 5. The Partners UCSF CTSI • Knowledge of the researcher, access to the data UCSF Library • Metadata expertise, programming resources UC3 • Preservations tools, services and expertise
- 6. Technical Infrastructure Perry Willett California Digital Library
- 7. DataShare Components Merritt: CDL EZID: CDL XTF: CDL, UCSF Library Ingest tool: UCSF Library
- 8. Merritt Repository Service Built on “micro-services” principles Content and format agnostic Has a UI and RESTful APIs to submit and retrieve content, and check statuses Can serve as either “dark” or “bright” archive Added public access, data use agreements, asynchronous downloads as part of Datashare project
- 9. EZID Service for creation and management of long- term identifiers Currently supports ARKs and DOIs; other types in planning stages Registers DOIs with DataCite Has a UI and APIs with good documentation
- 10. XTF eXtensible Text Framework Developed and maintained by CDL Runs several CDL services: • eScholarship • Online Archive of California • Calisphere Faceted browsing, full-text search, other desirable features
- 13. Ingest tool Submitting content to a digital repository is hard and costly An attempt to simplify several aspects: • Digital object creation • Metadata creation • Object submission
- 15. Interactions for submission Creates Metadata Assembles Dataset Datacite Packages object Submits to Merritt Registers DOI and Metadata Ingest Requests DOI Tool Merritt Submits Metadata to EZID Requests ATOM feed for collection Receives DOI Gets ATOM feed Retrieves Metadata XTF EZID Index metadata
- 16. Process for Endusers Search, browse Request dataset download Fill out Data Use Agreement Receive dataset
- 20. Lessons learned Partnerships • Many hands make light work • Real users uncover hidden assumptions Scale • Object size • Number of files • Upload and download
- 21. If you build it, will they come? Angela Rizk-Jackson UCSF CTSI
- 22. What will it take? + Sketch by Juliana Olivera Silva via Flickr
- 23. Providing Incentives: Requirements Organization Data Access Requirement # UCSF Studies Funding NIH Grants >$500K (2003 on), Specific 318 (active programs projects) 693 (inactive) NSF All funded projects (2005 on) 19 Foundations All funded projects 3, 31, 19 (e.g. Moore, Gates, Hewlett) Publishing Nature All published studies (2009-2011) 58 Publishing Group (Nature, Science, etc.) Cell Press All published studies (2009-2011) 48 (Cell, Neuron, etc.) PNAS All published studies (2005-2011) 26
- 24. Providing Incentives: Visibility 01010010101 00110010100 10101001001 00110001111 Enhances collaborative opportunities 69% increase in citation rate for publications associated with shared data (Piwowar, 2007)
- 26. Providing Incentives: Preservation & Access
- 27. Providing Incentives: Institutional • Support researcher needs • Improved archiving efficiency • Cost savings UCLA Royce Hall photo courtesy of Adam Fagen via Flickr
- 28. Eliminating Barriers 1. Time / Effort - Minimal requirements - Specific tools (e.g. ingest) - Integrate into existing workflow 2. Control - Data Use Agreement - Centralized service 3. Cultural Paradigm - Outreach - Demonstrate value
- 30. Lessons Learned Don’t underestimate technical matters • Separating data & metadata Standards are not standard • Metadata schema (Dublin Core DataCite) • Interpretation Policy issues are ever-present • Data Ownership & Data Use Agreements • Privacy & Consent (Human subjects) Keep in mind the entire lifecycle: ALL users • Discoverability & interoperability • README File
- 31. Next Steps Outreach System enhancements • Design overhaul • Ingest mechanism • DUA menu Policy navigation Proof-of-concept
- 32. Discussion Topics What incentives have you found useful to encourage adoption of this type of resource? Are you using data use agreements? Uniform or individualized? Where do you see institutional data repositories fitting in the larger ecosystem?
- 33. More info Datashare: http://datashare.ucsf.edu CDL: http://www.cdlib.org • Merritt: https://merritt.cdlib.org • EZID: http://n2t.net/ezid • XTF: http://xtf.cdlib.org UCSF Library: http://www.library.ucsf.edu/ UCSF CTSI: http://ctsi.ucsf.edu/ NCATS – NIH Grant # UL1 TR000004
Editor's Notes
- Mission: enable individual researchers to share their research data sets with the global communityA researcher at UCSF. In his work as the Principal Investigator of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) he concluded that widespread data sharing can be achieved now, with great scientific and economic benefits. All ADNI raw data is immediately shared, without embargo, with all scientists in the world. The project is very successful: more than 300 publications have resulted from use of the ADNI data resource. This success demonstrates the feasibility and benefits of sharing data.Clinical and Translational Sciences InstituteWorking together to develop a resource that meets the needs of the researcher while leverging the
- Cell Press, Nature Publishing Group, PNASOver 100 papers published between 2009-11 in journals from 3 publishers that have data sharing requirementsSome researchers have national repositories for their data (e.g. GenBank) while others don’t.Campus focused on developing infrastructure for storing and analyzing data but not sharing it generally. Additionally, the current focus is on clinical data, especially anonymized data from the electronic health record, and not basic or social sciences data.
- CTSI: Mission is to accelerate the research enterprise and saw the sharing of data as one way to accomplish this mission. Library: Interest in as well as an extension of the support of the open access ‘UC3: provide the tools to the UC community to promote digital scholarship.
- Screenshot of eScholarship, running XTF
- Screenshot of Datashare, running XTF
- Datashare website; enduser selects title
- Full information on dataset; enduser selects download
- Data Use Agreement (DUA) for enduser.
- Fulfills requirements, existing and emerging
- Increases visibility of work
- The new TR Data Citation Index provides a mechanism to discover data for re-use in the same familiar fashion as discovering publications
- Long term preservation, easy access to your own dataMerritt repository is an active archival environ with format migration and integrity checks – a smart filing cabinet for digital assets
- Centralizing resources improves efficiency by streamlining/standardizing the process and saves money in the aggregateCurrently gather data to support this
- Metadata, data/metadataseparation, file size, DUA, Discoverability, interoperability, README
- Metadata, data/metadataseparation, file size, DUA, Discoverability, interoperability, README