1. Kevin Read, MLIS, MAS NYU Langone Health Twitter: @readkev
A cross-institutional data discovery collaboration:
Highlighting invisible research data
Supplementing EHR data for research
S24
Kevin Read, MLIS, MAS
NYU Langone Health

2. Disclosure
I have no relevant relationships with commercial interests to disclose.
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3. Learning Objectives
After participating in this session you should be better able to:
Describe an initiative designed to make research data more discoverable
Identify the benefits of a multisite data discovery initiative:
Highlighting institutional research data
Identifying high-value datasets that require additional resources
Informing national data discovery efforts
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4. The Data Discovery Problem
88% of datasets from NIH-funded publications were ‘invisible’
(>200,000 datasets)
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5. The Data Discovery Solution (partly)
datamed.org
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6. The Persistent Discovery Problem?
>200,000 unidentified datasets/yr
datamed.org
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7. NYU Data Catalog: A Solution
datacatalog.med.nyu.edu
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8. NYU Data Catalog: A Solution
datacatalog.med.nyu.edu
DOES NOT STORE DATA
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9. NYU Data Catalog: Dataset Types
External Datasets
NYU Datasets
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10. NYU Data Catalog: External Datasets
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11. NYU Data Catalog: Internal Datasets
NYU Datasets
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12. NYU Data Catalog: Types of Data
Population health data
Quality improvement data
Submissions to clinical registries
EHR data pulls for research
Epidemiology data
Clinical trials data
Geospatial data
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13. NYU Data Catalog: Types of Data
Population health data
Quality improvement data
Submissions to clinical registries
EHR data pulls for research
Epidemiology data
Clinical trials data
Geospatial data
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14. Non-NYU Patient Encounter External Data Transfers
EHR: EPIC
Analysis Datasets
NYU Patient Encounter
Clinical Data Request
Publications
Clinical
Data
Governance
Abstracted Data
Reports
Analysis Datasets
EDC
Publications
Reports
External Site
Non-NYU Patient Encounter
External Data Transfers
External Site
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15. NYU Data Catalog: EHR Datasets
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16. NYU Data Catalog: EHR Datasets
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17. NYU Data Catalog: Flexible Discovery
Administrative
Research
Software
Quality Improvement
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18. NYU Data Catalog: Open Source
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19. NYU Data Catalog: Interoperability
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20. NYU Data Catalog: DATS Interoperability
DATS Metadata Specifications
NYU Data Catalog Metadata
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21. NYU Data Catalog: Discovery Solution?
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22. NYU Data Catalog: Discovery Solution?
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23. NYU Data Catalog: Collaboration
Open Source
Interoperability
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24. Data Catalog Collaboration
Multisite Collaboration:
Data Catalog Collaboration

25. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Research, EHR, QI data
Data Catalog Collaboration

26. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Genomics data
Data Catalog Collaboration

27. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Data Catalog Collaboration
Research data

28. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Data Catalog Collaboration
Research data

29. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Data Catalog Collaboration
CTSI -
Clinical Research Institute

30. Data Catalog Collaboration
Multisite Collaboration:
Efforts
Data Catalog Collaboration
Research data

31. Data Catalog Collaboration
Multisite Collaboration:
Outcomes
Data Catalog Collaboration
Previously undiscoverable:
Research data
EHR data
Genomics Data
QI data

32. NYU Data Catalog Growth
>12k users
>55k page views
>400 researchers
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33. Data Catalog Model: Benefits
Provides low-barrier entree into data sharing Offers researchers with a level of control over their data Flexibility of the types of research data objects described Ideal for identifying high-value datasets Valuable for gauging data sharing challenges
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34. Future Directions Develop a Data Catalog Coordinating Center
Recruit additional institutions looking to improve data discovery
Develop QI/Research Arm:
Data discovery use cases
Data types
High value datasets
Data sharing workflows
Partner with national data discovery initiatives
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35. References
NYU Data Catalog: Read K, Contaxis N, L I, Larson C, LaPolla FWZ, Surkis A. NYU Data Catalog Lamb I, Larson C. Shining a light on scientific data: Building a data catalog to foster data sharing and reuse. Code4Lib. 2016;32. Available from:
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36. Email me at: kevin.read@med.nyu.edu
Thank you!
me at: